CN112905813A - Algorithm system serving multimedia materials based on block chain operation - Google Patents
Algorithm system serving multimedia materials based on block chain operation Download PDFInfo
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- CN112905813A CN112905813A CN202110256008.4A CN202110256008A CN112905813A CN 112905813 A CN112905813 A CN 112905813A CN 202110256008 A CN202110256008 A CN 202110256008A CN 112905813 A CN112905813 A CN 112905813A
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Abstract
The invention discloses an algorithm system serving multimedia materials based on block chain operation, which comprises a keyword module, a database module and an output module, wherein the database module comprises a capturing module, a labeling module and a weight calculation module. According to the invention, the matched and output information and the source are bound and associated through the set keyword matching information, and the associated source can read corresponding data through an algorithm, so that the traceable use effect of the whole system is formed.
Description
Technical Field
The invention relates to the field of block chains, in particular to an algorithm system serving multimedia materials based on block chain operation.
Background
Blockchains are a term of art in information technology. In essence, the system is a shared database, and the data or information stored in the shared database has the characteristics of 'unforgeability', 'whole-course trace', 'traceability', 'public transparency', 'collective maintenance', and the like. Based on the characteristics, the block chain technology lays a solid 'trust' foundation, creates a reliable 'cooperation' mechanism and has wide application prospect.
However, in order to ensure the security of data in the existing multimedia material algorithms, a more complex encryption algorithm is generally used, and neither a newly uploaded material of a user nor a material being downloaded by the user has a certain reliable traceability, and especially, analysis between an original edition and a pirate edition is less, and the material is easily stolen by people by other means.
Disclosure of Invention
The technical problem to be solved by the invention is to overcome the defects of the prior art and provide an algorithm system serving multimedia materials based on block chain operation.
In order to solve the technical problems, the invention provides the following technical scheme:
the invention relates to an algorithm system serving multimedia materials based on block chain operation, which comprises a keyword module, a database module and an output module, wherein the database module comprises a capturing module, a labeling module and a weight calculation module, and specifically comprises the following steps:
A. constructing a database, and transmitting target data to a server by using a web crawler technology or direct input of a user to form an integral database module;
B. classifying the database, preprocessing the information in the database module, constructing an LDA model algorithm to train and optimize hyper-parameters for information classification, obtaining an average number k, processing classified matrix data into hash functions through the hash algorithm, obtaining a key code for each classified hash function, and then associating the key code with a corresponding source direction to form feature code association, so that the classified data becomes a driving table, the source direction becomes a detection table, and the driving table and the detection table are in nested arrangement;
C. the method comprises the steps that data are matched, a keyword module converts characters input into a text box into a character string t, similar data in an LDA model are matched through a grabbing module after the character string t is edited and operated for k times according to input replacement or character deletion, the effect of grabbing information by a plurality of grabbing modules is formed, and then source information in a detection table is read through a marking module according to feature codes formed by the similar data in a driving mode;
D. and calculating and outputting weight information, when the source information pointed by the feature codes of the plurality of similar data is the same and the k value is smaller, increasing the weight values of the similar data, comparing the weight values calculated by the weight value calculation module with each other, directly outputting by the grabbing module with the highest weight value, and arranging the other data with lower weight values in a descending order according to the weight values.
As a preferred technical solution of the present invention, the calculation steps of the weight calculation module specifically include:
d1: setting weight basic values according to the operation times of the k value, arranging the weight basic values from the highest value of 10 to 1, and setting the weight basic values as the basic values of 1 when the k value exceeds ten times;
d2: and according to the information concentration principle, calculating the weight of the corresponding feature code according to factor analysis and a principal component method, wherein the percentage of the feature code with more factor accounts is larger, and multiplying the corresponding percentage by the basic weight value in D1 to obtain the final weight information.
As a preferred technical solution of the present invention, a semantic matrix is set in the LDA model algorithm in step B, the semantic matrix is encrypted by a hash algorithm to be expressed as key codes, the key codes are sequentially arranged to obtain a driving table, the detection table is a sum of source information of a plurality of key codes, and after the source information is processed by the hash algorithm, the detection table is obtained by correspondingly arranging the driving table for correlation between the driving table and the detection table.
Compared with the prior art, the invention has the following beneficial effects:
1: according to the invention, the matched and output information and the source are bound and associated through the set keyword matching information, and the associated source can read corresponding data through an algorithm, so that the traceable use effect of the whole system is formed.
2: the invention can encrypt the matching information and the source information through the encryption setting of the hash algorithm, so that the set source can not be forged by a user, and the invention has good reliability.
3: the weight calculation module provided by the invention can add weight calculation to the same information source, and after the original similarity calculation is added, new weight calculation can be carried out according to the importance and authority percentage of the information source, and the calculated output content has higher reliability.
Drawings
The accompanying drawings, which are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the description serve to explain the principles of the invention and not to limit the invention. In the drawings:
FIG. 1 is a schematic diagram of the system architecture of the present invention;
FIG. 2 is a schematic flow diagram of the present invention;
Detailed Description
The following description of the preferred embodiments of the present invention is provided for the purpose of illustration and description, and is in no way intended to limit the invention.
Example 1
The invention provides an algorithm system serving multimedia materials based on block chain operation, which comprises a keyword module, a database module and an output module, wherein the database module comprises a capturing module, a labeling module and a weight calculation module, and specifically comprises the following steps:
A. constructing a database, and transmitting target data to a server by using a web crawler technology or direct input of a user to form an integral database module;
B. classifying the database, preprocessing the information in the database module, constructing an LDA model algorithm to train and optimize hyper-parameters for information classification, obtaining an average number k, processing classified matrix data into hash functions through the hash algorithm, obtaining a key code for each classified hash function, and then associating the key code with a corresponding source direction to form feature code association, so that the classified data becomes a driving table, the source direction becomes a detection table, and the driving table and the detection table are in nested arrangement;
C. the method comprises the steps that data are matched, a keyword module converts characters input into a text box into a character string t, similar data in an LDA model are matched through a grabbing module after the character string t is edited and operated for k times according to input replacement or character deletion, the effect of grabbing information by a plurality of grabbing modules is formed, and then source information in a detection table is read through a marking module according to feature codes formed by the similar data in a driving mode;
D. calculating weight information and outputting, when the source information pointed by the feature codes of a plurality of similar data is the same and the k value is smaller, increasing the weight values of the similar data, comparing the weight values calculated by the weight value calculation module, directly outputting by the grabbing module with the highest weight value, and arranging other data with lower weight values according to the descending order of the weight values
The calculation steps of the weight calculation module specifically include:
d1: setting weight basic values according to the operation times of the k value, arranging the weight basic values from the highest value of 10 to 1, and setting the weight basic values as the basic values of 1 when the k value exceeds ten times;
d2: and according to the information concentration principle, calculating the weight of the corresponding feature code according to factor analysis and a principal component method, wherein the percentage of the feature code with more factor accounts is larger, and multiplying the corresponding percentage by the basic weight value in D1 to obtain the final weight information.
And B, setting a semantic matrix in the LDA model algorithm, encrypting the semantic matrix into key codes through a hash algorithm to express the key codes, arranging the key codes in sequence to obtain a driving table, and processing the source information through the hash algorithm to obtain a detection table which is used for correlating the driving table with the detection table and is correspondingly arranged according to the driving table.
Specifically, a user mainly inputs corresponding texts through a keyword module, the texts are converted into character strings t through the keyword module, the character strings t are compared with the semantics in the database module after being converted into the semantics, the comparison process mainly comprises the steps of editing operation times k on a target string t, a corresponding grabbing module is generated after each operation, after the grabbing module matches the corresponding semantics, the grabbing module obtains the source direction of the corresponding semantics in a detection table according to a driving table through a marking module, and finally, the editing operation times k and the source direction are both input into a weight calculation module, if the occupation ratio of the source number is large in the same source direction, the semantic proportion of the whole source direction in the character strings t is large, after the source direction is processed with the original editing operation times k, the information finally obtained by a plurality of weight calculation modules is arranged in a descending order through the weight number, the output information is presented in the way that all information is provided with information source directions, and the information from the same source is arranged adjacently, so that the output information is ensured to have stronger authority and reliability, and has the effects of traceability, strong encryption and public transparency.
Finally, it should be noted that: although the present invention has been described in detail with reference to the foregoing embodiments, it will be apparent to those skilled in the art that changes may be made in the embodiments and/or equivalents thereof without departing from the spirit and scope of the invention. Any modification, equivalent replacement, or improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (3)
1. The utility model provides an algorithm system for serving multimedia materials based on block chain operation which characterized in that, algorithm system includes keyword module, database module and output module, database module includes snatchs module, mark module and weight calculation module, specifically includes following step:
A. constructing a database, and transmitting target data to a server by using a web crawler technology or direct input of a user to form an integral database module;
B. classifying the database, preprocessing the information in the database module, constructing an LDA model algorithm to train and optimize hyper-parameters for information classification, obtaining an average number k, processing classified matrix data into hash functions through the hash algorithm, obtaining a key code for each classified hash function, and then associating the key code with a corresponding source direction to form feature code association, so that the classified data becomes a driving table, the source direction becomes a detection table, and the driving table and the detection table are in nested arrangement;
C. the method comprises the steps that data are matched, a keyword module converts characters input into a text box into a character string t, similar data in an LDA model are matched through a grabbing module after the character string t is edited and operated for k times according to input replacement or character deletion, the effect of grabbing information by a plurality of grabbing modules is formed, and then source information in a detection table is read through a marking module according to feature codes formed by the similar data in a driving mode;
D. and calculating and outputting weight information, when the source information pointed by the feature codes of the plurality of similar data is the same and the k value is smaller, increasing the weight values of the similar data, comparing the weight values calculated by the weight value calculation module with each other, directly outputting by the grabbing module with the highest weight value, and arranging the other data with lower weight values in a descending order according to the weight values.
2. The system of claim 1, wherein the computing steps of the weight computing module comprise:
d1: setting weight basic values according to the operation times of the k value, arranging the weight basic values from the highest value of 10 to 1, and setting the weight basic values as the basic values of 1 when the k value exceeds ten times;
d2: and according to the information concentration principle, calculating the weight of the corresponding feature code according to factor analysis and a principal component method, wherein the percentage of the feature code with more factor accounts is larger, and multiplying the corresponding percentage by the basic weight value in D1 to obtain the final weight information.
3. The system of claim 1, wherein the LDA model algorithm of step B is provided with a semantic matrix, the semantic matrix is encrypted by a hash algorithm and expressed as key codes, the key codes are sequentially arranged to obtain a driving table, the detection table is a sum of source information of a plurality of key codes, and after the source information is processed by the hash algorithm, the detection table is obtained by correspondingly arranging the driving table and is used for correlation between the driving table and the detection table.
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Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
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| US20070005705A1 (en) * | 2005-06-17 | 2007-01-04 | Hung-Chih Yu | System and method of dynamically displaying an associated message in a message |
| US20200382279A1 (en) * | 2019-05-29 | 2020-12-03 | International Business Machines Corporation | Approximate hash verification of unused blockchain output |
| CN112134872A (en) * | 2020-09-16 | 2020-12-25 | 江苏省未来网络创新研究院 | Network system with multi-application-layer cloud computing function |
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Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US20070005705A1 (en) * | 2005-06-17 | 2007-01-04 | Hung-Chih Yu | System and method of dynamically displaying an associated message in a message |
| US20200382279A1 (en) * | 2019-05-29 | 2020-12-03 | International Business Machines Corporation | Approximate hash verification of unused blockchain output |
| CN112134872A (en) * | 2020-09-16 | 2020-12-25 | 江苏省未来网络创新研究院 | Network system with multi-application-layer cloud computing function |
Non-Patent Citations (1)
| Title |
|---|
| 来骥;马跃;吴舜;那琼澜;: "基于语义分析的运维数据关联知识库构建方法", 科学技术与工程, no. 19 * |
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