CN107545056B - New technology potential information analysis system and information analysis method - Google Patents
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Abstract
The invention discloses a new technical potential information analysis system and an information analysis method. The new technical potential information analysis method utilizes the new technical potential information analysis system, and comprises a new technical information collection and processing step, a characteristic classification analysis information processing step, a quality analysis information processing step, a field characteristic information processing step, a questionnaire survey information processing step, a terminal feedback step, an adjustment judgment step, a report updating step and a final report generating step.
Description
Technical Field
The invention relates to the technical field of new technical potential analysis, in particular to a new technical potential information analysis system and a new technical potential information analysis method.
Background
At present, the domestic and foreign markets are very eager for new technologies, particularly the new technologies, a large amount of idle funds exist, new technologies capable of investing capital are found by investment funds, public and private bases and financial groups of various public and private bases, various analysis and evaluation works are carried out by various consulting companies around the new technologies, however, the future potential of the new technologies is how much, whether the new technologies are worth the core problem of invested investment or not is difficult to be quickly understood and key-caught by investors, consulting companies and the like, and particularly on the basis of lack of deep understanding of relevant knowledge of the technologies. In the prior art, consulting companies perform reporting analysis for evaluating new technologies, but the analysis is often based on the subjective view of one or more people, and the reporting level is uneven according to different knowledge backgrounds of the people. In the prior art, some simple information systems or methods for generating new technology evaluation are provided, but the information systems or methods are too simple, the considered information is not comprehensive enough, no updating mechanism is provided, and no way is provided for making comprehensive and classified information for the new technology, so that the information can be conveniently called and consulted. The investors can most understand whether the new technology has the potential, the main indexes are the advantages and the disadvantages of the technology compared with the technology in the same field, and the technology has no mature technology or technology which is already invested. Based on the problems, the prior art does not have a systematic information system and method to deal with, potential investors of new technologies often only determine whether to invest based on some documents and report data mastered by the potential investors, and some counseling reports given by some law firms and counseling companies according to own experiences, and the effective systematic information system and information acquisition method are not used as effective references.
Disclosure of Invention
The invention aims to solve the problem that the judgment of the investment potential of the new technology in the prior art is not effective and the information system and the information acquisition method of the system are used as effective references, and provides a new technology evaluation information analysis system and an information analysis method which have strong pertinence to the new technology potential evaluation. The second purpose is that the information analysis in the prior art sometimes has too many automatic components, and the calculated result does not have confidence level in the view of the technicians in the field, for example, the superior/inferior analysis of the technology, the comparative advantage/superior analysis of other technologies in the same field, and the result of the pure and operation thereof may be too positive or too negative, which obviously deviates from the general cognition.
The invention provides a new technical potential information analysis system which is characterized by comprising the following components:
the central computer is responsible for all information processing and computer functions and is provided with a central memory.
The new technology information storage comprises a new technology information database which is used for recording the related information of the new technology as detailed as possible according to a basic index, and the basic index can be expanded when the storage allows.
A feature classification analysis memory comprises a feature classification analysis database, wherein a feature classification entry is newly established in the feature classification database for each new technology, the feature classification database is used for carrying out numerical processing on selected basic index information on the basis of information recorded item by item according to basic indexes in the new technology information database, new technologies with the information which is closer to the numerical processing and the quantity of which exceeds a preset threshold value are classified into a class so as to form a plurality of feature classifications, and the feature classification information is calculated and recorded in the feature classification entries in the feature classification analysis database.
The quality analysis memory comprises a quality analysis database, wherein a quality analysis item is newly established in the quality analysis database for each new technology, a plurality of quality values which are possibly related to the quality of the new technology are preset in the quality analysis database, each quality value is set in a value range from zero to a certain positive value or a certain negative value, and the corresponding quality value of each new technology is calculated, multiplied by a preset quantization factor Q and recorded in the quality analysis item.
The domain characteristic information storage comprises a domain characteristic database, wherein a domain characteristic analysis item is newly established for each new technology in the domain characteristic database, a domain characteristic information L strip which can most embody the potential of the new technology is preset in the domain characteristic database, the value of each domain characteristic information is set in a value interval from zero to a certain positive value, and the corresponding domain characteristic information of each new technology is recorded in the domain characteristic analysis item through calculation.
The questionnaire survey memory comprises a questionnaire survey database, a quality analysis simple report and a field characteristic simple report, wherein the questionnaire survey database is used for making the characteristic classification simple report according to the characteristic classification items, making the quality analysis simple report according to the quality analysis items, and making the field characteristic simple report according to the field characteristic analysis items, and the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are sent to a plurality of survey terminals by the questionnaire survey memory.
And the central calculator calculates and analyzes the confidence evaluation report and transmits the information to the feature classification analysis memory, the quality analysis memory and the field characteristic information memory.
The central calculator, the new technology information memory, the feature classification analysis memory, the quality analysis memory, the field characteristic information memory, the questionnaire survey memory and the survey terminals are in wireless communication connection.
Further, the L pieces of domain characteristic information are 5-20 pieces.
The invention also provides a new technical potential information analysis method using the new technical potential information analysis system, which is characterized by comprising the following steps:
1) the new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is sufficiently collected for new technologies in recent years, basic indexes are sufficiently created for each new technology, the basic indexes can be created as much as possible under the condition that memory space allows, the indexes can comprise simple indexes and compound indexes, collected information is filled into the basic indexes, and the collection and the information filling are repeatedly carried out until more than 90-95% of the basic indexes of any new technology are not empty.
2) And (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, feature classification information calculation is performed, which feature classification it belongs to is recorded in the feature classification entry, and new technologies which are not successfully classified are recorded in the feature classification entry as separate entries.
3) And (3) processing the quality analysis information: a good and bad analysis item is newly established for each new technology in the good and bad analysis database, a plurality of good and bad values possibly related to the good and bad of the new technology are preset in the good and bad analysis database, each good and bad value is set to a value range from zero to a certain positive value or a certain negative value, the corresponding good and bad value of each new technology is calculated, multiplied by a preset quantization factor Q, recorded in the good and bad analysis item, and stored as an independent item according to each new technology.
4) Processing the domain characteristic information: the method comprises the steps that a field characteristic analysis item is newly established for each new technology in a field characteristic database, 5-20 pieces of field characteristic information which can reflect the potential of the new technology most are preset in the field characteristic database, the value of each piece of field characteristic information is set to a value interval from zero to a certain positive value, the corresponding field characteristic information of each new technology is calculated, multiplied by a preset quantization factor R, recorded in the field characteristic analysis item, and stored as an independent item according to each new technology.
5) Questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory.
6) And a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to the feature classification analysis memory, the good and bad analysis memory and the domain characteristic information memory.
7) Adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); and if the item does not meet the condition that the average confidence coefficient under the same weight is higher than P%, correspondingly adjusting the characteristic classification analysis information processing step, the quality analysis information processing step and the field characteristic information processing step, and entering the step (8).
8) And updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; and (6) returning.
9) And a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
Further, steps (1) to (9) are specifically.
1) The new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is fully collected for the new technology in recent years, a basic index is fully created for each new technology, the basic index can be created as much as possible under the condition that the memory space allows, the index can comprise a simple index and a compound index, the collected information is filled into the basic index, and the collection and the information filling are repeatedly carried out until more than 90% of the basic indexes of any new technology are not empty; the information collection range of the basic index includes, but is not limited to, expert evaluation of new technology, market prospect information, popularity information, implementation technology difficulty, plagiarism difficulty and user prospect information.
2) And (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, calculating the characteristic classification information, recording which characteristic classification the new technology belongs to in the characteristic classification entry, and recording the new technology which is not successfully classified in the characteristic classification entry in a single entry; the M is 10 or more and 20 or less, the N term is an integer and the minimum value is 2, and a new technique for describing an individual entry is also given a class name.
3) And (3) processing the quality analysis information: establishing a good and bad analysis item for each new technology in the good and bad analysis database, presetting a plurality of good and bad values possibly related to the good and bad of the new technology in the good and bad analysis database, setting a value interval from zero to a certain positive value or a certain negative value for each good and bad value, calculating the corresponding good and bad value of each new technology, multiplying the value by a preset quantization factor Q, recording the value in the good and bad analysis item, and storing the value as an independent item according to each new technology; the initial value of the quantization factor Q is determined by the average deviation value of each difference of the corresponding index values of each new technique classified with respect to the same feature of each new technique of step (2), and the initial value of the quantization factor Q is equal to 1.
4) Processing the domain characteristic information: newly building a field characteristic analysis item for each new technology in the field characteristic database, presetting 5-20 pieces of field characteristic information which can most reflect the potential of the new technology in the field characteristic database, setting the value of each piece of field characteristic information to a value interval from zero to a certain positive value, calculating the corresponding field characteristic information of each new technology, multiplying the calculated field characteristic information by a preset quantization factor R, recording the calculated field characteristic information in the field characteristic analysis item, and storing the calculated field characteristic information as an independent item according to each new technology; the initial value of the quantization factor R can ensure that at least 80% of values in all the domain characteristic information are within 40-100% of the value interval from zero to a certain positive value.
5) Questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory.
6) And a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to the feature classification analysis memory, the good and bad analysis memory and the domain characteristic information memory.
7) Adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); if the average confidence coefficient which does not meet the condition of the same weight is higher than P%, correspondingly adjusting the steps of processing the feature classification analysis information, processing the quality analysis information and processing the domain characteristic information, and entering the step (8); p is greater than or equal to 60 and less than or equal to 70.
8) And updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; returning to the step (6);
9) and a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
Further, in the step (6), while the confidence score is collected, higher or lower evaluations for the quality analysis simple report and the domain feature simple report are given, and the higher or lower evaluation values are weighted and averaged to obtain a higher or lower average evaluation value, which is used for guiding the value of Q to be modified and the value of R to be modified in the step (8).
The invention has the advantages that the invention can be mainly divided into two points, the prior art does not have a comprehensive information classification system, the prior information is often embodied as a patent report, the patent report has no instantaneity and cannot be updated in real time, the invention not only provides a specific system, but also provides an embodying method of the novel technology with the most potential information, and the method also has a confidence feedback adjustment step, so that the result is very practical and meaningful, and an applicant searches, does not see a similar technology in the prior art, and does not have technical inspiration in the prior art. The present application is invented by the applicant based on the problems encountered by the applicant in the practice of new technology mining, and has enough innovation.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
Fig. 1 is a flowchart of a new technical potential information analysis method of the present invention.
Detailed Description
The preferred embodiments of the present invention will be described in detail below with reference to the accompanying drawings so that the advantages and features of the present invention can be more easily understood by those skilled in the art, and the scope of the present invention will be more clearly and clearly defined.
Example 1
A new technology potential information analysis system is characterized by comprising the following components:
the central computer is responsible for all information processing and computer functions and is provided with a central memory. The central calculator is responsible for the computing function of the whole system, can be provided with a buffer and a task processor for queuing a plurality of tasks for processing, can also be provided with a plurality of computing cores and a self-contained buffer, and can autonomously process and feed back a plurality of task requirements.
The new technology information storage comprises a new technology information database which is used for recording the related information of the new technology as detailed as possible according to a basic index, and the basic index can be expanded when the storage allows. The possible form of the expansion is a row of storage card expansion slots, which comprise tf, sd and other storage card expansions, and can also be a row of hard disk slots which can be externally connected with a plurality of common hard disks/solid state disks. For convenience of subsequent processing, the information related to the new technology is recorded as comprehensively as possible, including domain characteristic information of the new technology, a principle of the new technology, component elements of the new technology, research and development maturity and research and development prospective analysis results of the new technology, public acceptance degree of the new technology, popularization feasibility analysis results of the new technology, popular investigation analysis results of the new technology, financing return rate of the new technology, life cycle prediction of the new technology, intellectual property protection possibility and protection difficulty of the new technology, possibility analysis reports of the new technology being emulated/copied, and the like.
A feature classification analysis memory comprises a feature classification analysis database, wherein a feature classification entry is newly established in the feature classification database for each new technology, the feature classification database is used for carrying out numerical processing on selected basic index information on the basis of information recorded item by item according to basic indexes in the new technology information database, new technologies with the information which is closer to the numerical processing and the quantity of which exceeds a preset threshold value are classified into a class so as to form a plurality of feature classifications, and the feature classification information is calculated and recorded in the feature classification entries in the feature classification analysis database. The classification of features is most intuitively made by a person who wants to understand the new technology with some other techniques as a reference, and the new technology can be intuitively understood compared with the known technology, although the development prospect of the new technology with the classification of features is actually different. Specifically, the characteristic classification is, for example, typing, and the typing information can classify the technologies with similar characteristics into one class, or the technologies with similar calculated values are considered to be the same typing technology, which is a relatively effective way of providing reference information, for example, for a lipstick-type nail clipper, the numerical analysis shows that the technology is similar to the numerical values of the existing lipstick-type portable toothbrush, and the classification calculation can consider the investment potential and the development potential of the lipstick-type nail clipper with reference to the development condition of the lipstick-type portable toothbrush.
The quality analysis memory comprises a quality analysis database, wherein a quality analysis item is newly established in the quality analysis database for each new technology, a plurality of quality values which are possibly related to the quality of the new technology are preset in the quality analysis database, each quality value is set in a value range from zero to a certain positive value or a certain negative value, and the corresponding quality value of each new technology is calculated, multiplied by a preset quantization factor Q and recorded in the quality analysis item. Although the method is simple in appearance, the information of the advantage and disadvantage analysis is very valuable for judging the development potential of a new technology, and is important information for investors to choose whether to invest or not, the advantage and disadvantage analysis can establish a vector for analyzing the outstanding advantages and disadvantages of the technology, and the data can intuitively give suggestions for the prospect of the technology. For example, the advantages here may be that there is no technology of the same kind competing with it, the return on investment is extremely high, the recovery period of investment is short, the promotion is easy, the cost required for promotion is small, and the disadvantages here may be that the promotion is difficult and the consumption habit of the target market is not met.
The domain characteristic information storage comprises a domain characteristic database, wherein a domain characteristic analysis item is newly established for each new technology in the domain characteristic database, a domain characteristic information L strip which can most embody the potential of the new technology is preset in the domain characteristic database, the value of each domain characteristic information is set in a value interval from zero to a certain positive value, and the corresponding domain characteristic information of each new technology is recorded in the domain characteristic analysis item through calculation. Each new technology has its specific adaptive field, which is equivalent to judging the coordinate system of the technology, whether the coordinate system meets the requirements of the field, whether the coordinate system has advantages in the field is one of the most important judgment indexes, for example, if the portable toothbrush is analyzed to have many advantages, but the portable toothbrush is put into the specific field to be examined, whether the manufacturing yield most concerned in the field is high enough, whether the material is cheap and environment-friendly, whether the industrial design follows the trend, and if the portable toothbrush does not perform enough on the special points of the field, the investment prospect of the technology can be limited.
The questionnaire survey memory comprises a questionnaire survey database, a quality analysis simple report and a field characteristic simple report, wherein the questionnaire survey database is used for making the characteristic classification simple report according to the characteristic classification items, making the quality analysis simple report according to the quality analysis items, and making the field characteristic simple report according to the field characteristic analysis items, and the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are sent to a plurality of survey terminals by the questionnaire survey memory. The simple reports are the reports of three important information in the three memories, which have an extremely important reference value for whether the technology is worth investing, but if the evaluation stage of confidence confirmation is not carried out, the reasonable or not of the results is difficult to grasp, the results are possibly too pessimistic than normal, or the results are optimistic than normal, most of the displayed results are unreasonable, and the simple reports can happen.
And the central calculator calculates and analyzes the confidence evaluation report and transmits the information to the feature classification analysis memory, the quality analysis memory and the field characteristic information memory. The invention is characterized in that a special system and a method arrange characteristic classification information, quality analysis information and field characteristic information, and simultaneously feed back confidence coefficients of the information through interaction of the investigation terminal.
The central calculator, the new technology information memory, the feature classification analysis memory, the quality analysis memory, the field characteristic information memory, the questionnaire survey memory and the survey terminals are in wireless communication connection.
Further, the L pieces of domain characteristic information are 5-20 pieces.
The invention also provides a new technical potential information analysis method using the new technical potential information analysis system, which is characterized by comprising the following steps:
1) the new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is sufficiently collected for new technologies in recent years, basic indexes are sufficiently created for each new technology, the basic indexes can be created as much as possible under the condition that memory space allows, the indexes can comprise simple indexes and compound indexes, collected information is filled into the basic indexes, and the collection and the information filling are repeatedly carried out until more than 90-95% of the basic indexes of any new technology are not empty.
2) And (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, feature classification information calculation is performed, which feature classification it belongs to is recorded in the feature classification entry, and new technologies which are not successfully classified are recorded in the feature classification entry as separate entries.
3) And (3) processing the quality analysis information: a good and bad analysis item is newly established for each new technology in the good and bad analysis database, a plurality of good and bad values possibly related to the good and bad of the new technology are preset in the good and bad analysis database, each good and bad value is set to a value range from zero to a certain positive value or a certain negative value, the corresponding good and bad value of each new technology is calculated, multiplied by a preset quantization factor Q, recorded in the good and bad analysis item, and stored as an independent item according to each new technology.
4) Processing the domain characteristic information: the method comprises the steps that a field characteristic analysis item is newly established for each new technology in a field characteristic database, 5-20 pieces of field characteristic information which can reflect the potential of the new technology most are preset in the field characteristic database, the value of each piece of field characteristic information is set to a value interval from zero to a certain positive value, the corresponding field characteristic information of each new technology is calculated, multiplied by a preset quantization factor R, recorded in the field characteristic analysis item, and stored as an independent item according to each new technology.
5) Questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory.
6) And a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to the feature classification analysis memory, the good and bad analysis memory and the domain characteristic information memory.
7) Adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); and if the item does not meet the condition that the average confidence coefficient under the same weight is higher than P%, correspondingly adjusting the characteristic classification analysis information processing step, the quality analysis information processing step and the field characteristic information processing step, and entering the step (8).
8) And updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; and (6) returning.
9) And a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
Further, the steps (1) to (9) are specifically:
1) the new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is fully collected for the new technology in recent years, a basic index is fully created for each new technology, the basic index can be created as much as possible under the condition that the memory space allows, the index can comprise a simple index and a compound index, the collected information is filled into the basic index, and the collection and the information filling are repeatedly carried out until more than 90% of the basic indexes of any new technology are not empty; the information collection range of the basic index includes, but is not limited to, expert evaluation of new technology, market prospect information, popularity information, implementation technology difficulty, plagiarism difficulty and user prospect information.
2) And (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, calculating the characteristic classification information, recording which characteristic classification the new technology belongs to in the characteristic classification entry, and recording the new technology which is not successfully classified in the characteristic classification entry in a single entry; the M is 10 or more and 20 or less, the N term is an integer and the minimum value is 2, and a new technique for describing an individual entry is also given a class name.
3) And (3) processing the quality analysis information: establishing a good and bad analysis item for each new technology in the good and bad analysis database, presetting a plurality of good and bad values possibly related to the good and bad of the new technology in the good and bad analysis database, setting a value interval from zero to a certain positive value or a certain negative value for each good and bad value, calculating the corresponding good and bad value of each new technology, multiplying the value by a preset quantization factor Q, recording the value in the good and bad analysis item, and storing the value as an independent item according to each new technology; the initial value of the quantization factor Q is determined by the average deviation value of each difference of the corresponding index values of each new technique classified with respect to the same feature of each new technique of step (2), and the initial value of the quantization factor Q is equal to 1.
4) Processing the domain characteristic information: newly building a field characteristic analysis item for each new technology in the field characteristic database, presetting 5-20 pieces of field characteristic information which can most reflect the potential of the new technology in the field characteristic database, setting the value of each piece of field characteristic information to a value interval from zero to a certain positive value, calculating the corresponding field characteristic information of each new technology, multiplying the calculated field characteristic information by a preset quantization factor R, recording the calculated field characteristic information in the field characteristic analysis item, and storing the calculated field characteristic information as an independent item according to each new technology; the initial value of the quantization factor R can ensure that at least 80% of values in all the domain characteristic information are within 40-100% of the value interval from zero to a certain positive value.
5) Questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory.
6) And a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to the feature classification analysis memory, the good and bad analysis memory and the domain characteristic information memory.
7) Adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); if the average confidence coefficient which does not meet the condition of the same weight is higher than P%, correspondingly adjusting the steps of processing the feature classification analysis information, processing the quality analysis information and processing the domain characteristic information, and entering the step (8); p is greater than or equal to 60 and less than or equal to 70.
8) And updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; and (6) returning.
9) And a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
Further, in the step (6), while the confidence score is collected, higher or lower evaluations for the quality analysis simple report and the domain feature simple report are given, and the higher or lower evaluation values are weighted and averaged to obtain a higher or lower average evaluation value, which is used for guiding the value of Q to be modified and the value of R to be modified in the step (8).
The above description is only an embodiment of the present invention, but the scope of the present invention is not limited thereto, and any changes or substitutions that are not thought of through the inventive work should be included in the scope of the present invention. Therefore, the protection scope of the present invention shall be subject to the protection scope defined by the claims.
Claims (3)
1. A new technology potential information analysis method which utilizes a new technology potential information analysis system for analysis, the system comprising the following components:
a central computer, which is responsible for all information processing and computer functions and is provided with a central memory;
a new technology information storage, which comprises a new technology information database and is used for recording the related information of the new technology as detailed as possible according to a basic index, wherein the basic index can be expanded when the storage allows;
a feature classification analysis memory which comprises a feature classification analysis database, wherein a feature classification entry is newly established in the feature classification database for each new technology, the feature classification database is used for carrying out numerical processing on selected basic index information on the basis of information which is recorded in the new technology information database one by one according to basic indexes, and classifying new technologies which are closer in information after numerical processing and have the quantity exceeding a preset threshold value into a class so as to form a plurality of feature classifications, and the feature classification information is calculated and recorded in the feature classification entries in the feature classification analysis database;
the quality analysis memory comprises a quality analysis database, wherein a quality analysis item is newly established in the quality analysis database for each new technology, a plurality of quality values possibly related to the quality of the new technology are preset in the quality analysis database, each quality value is set in a value interval from zero to a certain positive value or a certain negative value, and the corresponding quality value of each new technology is calculated, multiplied by a preset quantization factor Q and recorded in the quality analysis item;
the domain characteristic information storage comprises a domain characteristic database, wherein a domain characteristic analysis item is newly established for each new technology in the domain characteristic database, a domain characteristic information L strip which can most embody the potential of the new technology is preset in the domain characteristic database, the value of each domain characteristic information is set in a value interval from zero to a certain positive value, and the corresponding domain characteristic information of each new technology is calculated and recorded in the domain characteristic analysis item;
the questionnaire survey memory comprises a questionnaire survey database, a quality analysis simple report and a field characteristic simple report, wherein the questionnaire survey database is used for making the characteristic classification simple report according to the characteristic classification items, making the quality analysis simple report according to the quality analysis items, and making the field characteristic simple report according to the field characteristic analysis items;
the central calculator calculates and analyzes the confidence evaluation report and transmits the information to the feature classification analysis memory, the quality analysis memory and the field characteristic information memory;
the central calculator, the new technology information memory, the feature classification analysis memory, the quality analysis memory, the field characteristic information memory, the questionnaire survey memory and the plurality of survey terminals are in wireless communication connection;
the number of the L pieces of domain characteristic information is 5-20;
characterized in that the analysis method comprises the following steps:
1) the new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is fully collected for the new technology in recent years, a basic index is fully created for each new technology, the basic index can be created as much as possible under the condition of memory space allowance, the index can comprise a simple index and a compound index, the collected information is filled into the basic index, and the collection and the information filling are repeatedly carried out until more than 90-95% of the basic indexes of any new technology are not empty;
2) and (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, calculating the characteristic classification information, recording which characteristic classification the new technology belongs to in the characteristic classification entry, and recording the new technology which is not successfully classified in the characteristic classification entry in a single entry;
3) and (3) processing the quality analysis information: establishing a good and bad analysis item for each new technology in the good and bad analysis database, presetting a plurality of good and bad values possibly related to the good and bad of the new technology in the good and bad analysis database, setting a value interval from zero to a certain positive value or a certain negative value for each good and bad value, calculating the corresponding good and bad value of each new technology, multiplying the value by a preset quantization factor Q, recording the value in the good and bad analysis item, and storing the value as an independent item according to each new technology;
4) processing the domain characteristic information: newly building a field characteristic analysis item for each new technology in the field characteristic database, presetting 5-20 pieces of field characteristic information which can most reflect the potential of the new technology in the field characteristic database, setting the value of each piece of field characteristic information to a value interval from zero to a certain positive value, calculating the corresponding field characteristic information of each new technology, multiplying the calculated field characteristic information by a preset quantization factor R, recording the calculated field characteristic information in the field characteristic analysis item, and storing the calculated field characteristic information as an independent item according to each new technology;
5) questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory;
6) and a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to a feature classification analysis memory, a good and bad analysis memory and a domain characteristic information memory;
7) adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); if the average confidence coefficient which does not meet the condition of the same weight is higher than P%, correspondingly adjusting the steps of processing the feature classification analysis information, processing the quality analysis information and processing the domain characteristic information, and entering the step (8);
8) and updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; returning to the step (6);
9) and a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
2. The method for analyzing new technical potential information according to claim 1, wherein the steps (1) to (9) are specifically:
1) the new technology information collection and processing steps are as follows: through sufficient research and demonstration, information is fully collected for the new technology in recent years, a basic index is fully created for each new technology, the basic index can be created as much as possible under the condition that the memory space allows, the index can comprise a simple index and a compound index, the collected information is filled into the basic index, and the collection and the information filling are repeatedly carried out until more than 90% of the basic indexes of any new technology are not empty; the information collection range of the basic index includes, but is not limited to, expert evaluation of new technology, market prospect information, popularity information, implementation technology difficulty, plagiarism difficulty and user prospect information;
2) and (3) processing the characteristic classification analysis information: selecting all of the aforementioned base indices, selecting a quantifiable index in which direct numeralization and step numeralization can be performed, creating a new feature classification item for each new technology in the feature classification database, performing numerical processing on index information in a numerically-processed index, classifying the new technologies of which the difference of each corresponding index value does not exceed M% and the total number exceeds N items after numerical processing into a class to form a feature classification, the feature classification information is calculated, recorded in a feature classification entry in a feature classification analysis database, for each new technology in the new technology information database, calculating the characteristic classification information, recording which characteristic classification the new technology belongs to in the characteristic classification entry, and recording the new technology which is not successfully classified in the characteristic classification entry in a single entry; m is greater than or equal to 10 and less than or equal to 20, N is an integer and the minimum value is 2, and a new technology for recording an individual entry is also given a class name;
3) and (3) processing the quality analysis information: establishing a good and bad analysis item for each new technology in the good and bad analysis database, presetting a plurality of good and bad values possibly related to the good and bad of the new technology in the good and bad analysis database, setting a value interval from zero to a certain positive value or a certain negative value for each good and bad value, calculating the corresponding good and bad value of each new technology, multiplying the value by a preset quantization factor Q, recording the value in the good and bad analysis item, and storing the value as an independent item according to each new technology; the initial value of the quantization factor Q is determined by the average deviation value of each difference of the corresponding index values of each new technology classified relative to the same feature of each new technology in step (2), and the initial value of the quantization factor Q is equal to 1;
4) processing the domain characteristic information: newly building a field characteristic analysis item for each new technology in the field characteristic database, presetting 5-20 pieces of field characteristic information which can most reflect the potential of the new technology in the field characteristic database, setting the value of each piece of field characteristic information to a value interval from zero to a certain positive value, calculating the corresponding field characteristic information of each new technology, multiplying the calculated field characteristic information by a preset quantization factor R, recording the calculated field characteristic information in the field characteristic analysis item, and storing the calculated field characteristic information as an independent item according to each new technology; the initial value of the quantization factor R can ensure that at least 80% of values in all the domain characteristic information are within 40-100% of the value interval from zero to a certain positive value;
5) questionnaire survey information processing step: in the step, a questionnaire simple report is newly created for each new technology, a characteristic classification simple report is made according to the characteristic classification items, a quality analysis simple report is made according to the quality analysis items, and a field characteristic simple report is made according to the field characteristic analysis items, wherein the characteristic classification simple report, the quality analysis simple report and the field characteristic simple report are all merged into the questionnaire simple report and are sent to a plurality of investigation terminals by a questionnaire survey memory;
6) and a terminal feedback step: in the step, a plurality of survey terminals are used for receiving the questionnaire simple report and displaying the questionnaire simple report to a terminal user, the terminal user gives confidence score, the central calculator collects the confidence score from all the terminals and generates a confidence evaluation report, and the central calculator decomposes the confidence evaluation report into a feature classification confidence evaluation report, a good and bad analysis confidence evaluation report and a domain characteristic confidence evaluation report, and respectively transmits the feature classification confidence evaluation report, the good and bad analysis confidence evaluation report and the domain characteristic confidence evaluation report to a feature classification analysis memory, a good and bad analysis memory and a domain characteristic information memory;
7) adjusting and judging: respectively judging whether the average confidence coefficient under the same weight is higher than P% in a feature classification analysis database, a good and bad analysis confidence coefficient evaluation database and a field characteristic database, if so, not modifying the feature classification simple report, the good and bad analysis simple report and the field characteristic simple report, and entering the step (9); if the average confidence coefficient which does not meet the condition of the same weight is higher than P%, correspondingly adjusting the steps of processing the feature classification analysis information, processing the quality analysis information and processing the domain characteristic information, and entering the step (8); p is greater than or equal to 60 and less than or equal to 70;
8) and updating the report: if the average confidence coefficient which does not meet the condition under the same weight in the step (7) is higher than P%, correspondingly returning the unsatisfied feature classification simple report, the goodness and badness analysis simple report and the field feature simple report to a feature classification database, a goodness and badness analysis database and a field feature database, modifying the values of M and N for the feature classification database, and regenerating the feature classification simple report; for the quality analysis database, modifying the value of Q, and regenerating a quality analysis simple report; for the domain characteristic database, modifying the value of R, and regenerating a domain characteristic simple report; returning to the step (6);
9) and a final report generation step: and on the premise of meeting the requirements of a feature classification simple report, a quality analysis simple report and a field characteristic simple report of which the average confidence coefficient is higher than P% under the same weight, combining the information of each new technology in the new technology information database to generate a potential information analysis report of each new technology.
3. A new technology potential information analysis method according to claim 2, characterized in that:
in the step (6), while the confidence score is collected, higher or lower evaluations for the quality analysis simple report and the field characteristic simple report are given, and the higher or lower evaluation values are weighted and averaged to obtain a higher or lower average evaluation value, which is used for guiding the modification of the value of Q and the modification of the value of R in the step (8).
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