CN112182336B - Beijing pattern pedigree sorting and classifying system - Google Patents
Beijing pattern pedigree sorting and classifying system Download PDFInfo
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Abstract
The invention relates to the field of Beijing pattern pedigree, in particular to a Beijing pattern pedigree sorting system, which comprises the following components: the Beijing opera pattern spectrum crawler module is used for digging corresponding Beijing opera pattern spectrum data on each network base station based on a preset Beijing opera pattern spectrum crawling model to generate a Beijing opera pattern spectrum data set; the Beijing opera pattern spectrum classification module is used for realizing the identification of the Beijing opera pattern spectrum factors in the Beijing opera pattern spectrum data set based on the Beijing opera pattern spectrum model D_acceptance_V3_coco and realizing the arrangement and classification of the Beijing opera pattern spectrum according to the identification result; the Beijing opera pattern spectrum deriving module is used for realizing the segmentation, combination and arrangement of the Beijing opera pattern spectrum factors based on a preset template, generating a new Beijing opera pattern spectrum and expanding a Beijing opera pattern spectrum database. The invention realizes the automatic collection, arrangement and classified storage of the Beijing opera pattern spectrum data, and greatly facilitates the use of staff while greatly reducing the manual workload.
Description
Technical Field
The invention relates to the field of Beijing pattern pedigree, in particular to a Beijing pattern pedigree sorting system.
Background
At present, the arrangement of the Beijing pattern spectrum generally depends on human work, the work load is large, meanwhile, data omission is easy to occur, and the design process of the Beijing pattern spectrum also needs to be drawn and spliced manually.
Disclosure of Invention
In order to solve the problems, the invention provides a Beijing pattern pedigree sorting system, which realizes automatic collection, sorting and sorting storage of Beijing pattern pedigree data, can greatly reduce the manual workload and simultaneously greatly facilitates the use of staff.
In order to achieve the above purpose, the technical scheme adopted by the invention is as follows:
a kyoto pattern pedigree arrangement classification system, comprising:
the Beijing opera pattern spectrum crawler module is used for digging corresponding Beijing opera pattern spectrum data on each network base station based on a preset Beijing opera pattern spectrum crawling model to generate a Beijing opera pattern spectrum data set;
the Beijing opera pattern spectrum classification module is used for realizing the identification of the Beijing opera pattern spectrum factors in the Beijing opera pattern spectrum data set based on the Beijing opera pattern spectrum model D_acceptance_V3_coco and realizing the arrangement and classification of the Beijing opera pattern spectrum according to the identification result;
the Beijing opera pattern spectrum deriving module is used for realizing the segmentation, combination and arrangement of the Beijing opera pattern spectrum factors based on a preset template, generating a new Beijing opera pattern spectrum and expanding a Beijing opera pattern spectrum database.
Further, the Beijing opera pattern spectrum crawling model comprises a time identification model and a pattern spectrum crawling model, wherein the time identification model is used for realizing framing of data meeting a time threshold in the network base station based on the last data crawling time, and the pattern spectrum crawling model is used for mining corresponding Beijing opera pattern spectrum data in the framed data.
Further, the method further comprises the following steps:
and the crawling model training module is used for training and acquiring a pattern spectrum crawling model based on the recorded Beijing opera pattern spectrum factor set.
Further, the DSSD-acceptance-V3-coco model adopts a DSSD target detection algorithm, the acceptance-V3 deep neural network is pre-trained by a coco data set, then the model is trained by a data set prepared previously, various parameters in the deep neural network are finely adjusted, and finally a suitable target detection model for detecting the Beijing pattern spectrum factors is obtained.
Further, the Beijing opera pattern spectrum classifying module is used for realizing the arrangement and classification of the Beijing opera pattern spectrum based on the type of the Beijing opera pattern spectrum factors or the type and arrangement rules of the Beijing opera pattern spectrum factors by the multi-layer perceptron, and eliminating repeated Beijing opera pattern spectrum data.
Further, the Beijing opera pattern spectrum generated by the Beijing opera pattern spectrum deriving module is independently configured with a database, each Beijing opera pattern spectrum factor in the Beijing opera pattern spectrum carries a corresponding source mark, and the source Beijing opera pattern spectrum factor can be checked by clicking the mark.
Further, the method further comprises the following steps:
and the Beijing pattern spectrum query module is used for realizing the query of the Beijing pattern spectrum, supporting the query of texts, patterns, audios and videos, and feeding back query results in the form of an EXCEL table, wherein each query result comprises query source data and corresponding query results.
Further, the method further comprises the following steps:
and the data positioning module is used for finding a proper position for the corresponding Beijing pattern spectrum data in the data according to the type of the Beijing pattern spectrum factors or the type and arrangement rules of the Beijing pattern spectrum factors, finding similar data points for the Beijing pattern spectrum data and establishing the relation between the Beijing pattern spectrum data and the similar data points.
The invention has the following beneficial effects:
1) Through internet technology, tracking and rapid collection of the Beijing opera pattern spectrum data are realized, so that the automatic integration of the existing Beijing opera pattern spectrum data can be realized, the manual workload can be greatly reduced, and meanwhile, missing data can be reduced as much as possible.
2) The automatic classified storage of the Beijing opera pattern spectrum data is realized through a DSSD_acceptance_V3_coco model, and the artificial workload can be greatly reduced.
3) The method has the function of deriving the Beijing pattern spectrum, can realize the segmentation, combination and arrangement of the Beijing pattern spectrum factors based on a preset template and generate a new Beijing pattern spectrum, thereby realizing the expansion of a Beijing pattern spectrum database and providing ideas for the innovation of the Beijing pattern spectrum.
4) The Beijing opera pattern spectrum inquiry function is configured, the inquiry of texts, patterns, audio and video is supported, and the use of staff is greatly facilitated.
Drawings
FIG. 1 is a system block diagram of a Beijing opera pattern pedigree sorting system according to example 1 of the present invention.
Detailed Description
The present invention will be described in further detail with reference to examples in order to make the objects and advantages of the present invention more apparent. It should be understood that the specific embodiments described herein are for purposes of illustration only and are not intended to limit the scope of the invention.
Example 1
As shown in fig. 1, a kyoto pattern pedigree sorting system, comprising:
the crawling model training module is used for training and obtaining a pattern spectrum crawling model based on the recorded Beijing opera pattern spectrum factor set;
the Beijing opera pattern spectrum crawler module is used for digging corresponding Beijing opera pattern spectrum data on each network base station based on a preset Beijing opera pattern spectrum crawling model to generate a Beijing opera pattern spectrum data set;
the Beijing opera pattern spectrum classification module is used for realizing the identification of the Beijing opera pattern spectrum factors in the Beijing opera pattern spectrum data set based on the Beijing opera pattern spectrum model D_acceptance_V3_coco and realizing the arrangement and classification of the Beijing opera pattern spectrum according to the identification result; after the identification is finished, each Beijing pattern spectrum image carries a mark frame of a Beijing pattern spectrum factor, a user clicks the image to realize the appearance of the mark frame, and the mark frame is in a hidden state in other states; after finishing sorting of one batch, the system automatically generates a data set to be checked, namely, eliminates image sets of the area where the mark frame is located, and a user can recognize whether new Beijing opera pattern spectrum factors exist in the image sets through checking the image sets, if so, a text frame selection mode is adopted to generate the new Beijing opera pattern spectrum factors, so that updating of a pattern spectrum crawling model is realized.
The data positioning module is used for finding a proper position for corresponding Beijing opera pattern spectrum data in the data according to the type of the Beijing opera pattern spectrum factors or the type and arrangement rules of the Beijing opera pattern spectrum factors, finding similar data points for the Beijing opera pattern spectrum data and establishing the relation between the Beijing opera pattern spectrum factors and the similar data points; the data positioning module realizes data positioning based on the faceting technology, and accurately positions data by calculating faceting distances among different data terms; when positioning data, selecting corresponding terms under the constraint of known facets, so as to complete description of required data, and returning corresponding data if the selection is successful; if the selection is unsuccessful, the system calculates the similarity of terms according to the synonym dictionary and the conceptual distance map to form new positioning information;
the Beijing opera pattern spectrum deriving module is used for realizing the segmentation, combination and arrangement of the Beijing opera pattern spectrum factors based on a preset template, generating a new Beijing opera pattern spectrum and expanding a Beijing opera pattern spectrum database;
the Beijing pattern spectrum query module is used for realizing the query of the Beijing pattern spectrum, supporting the query of texts, patterns, audios and videos, and feeding back query results in the form of an EXCEL table, wherein each query result comprises query source data and corresponding query results;
and the central processing module is used for coordinating the work of the modules.
In this embodiment, the kyoto pattern spectrum crawling model includes a time identification model and a pattern spectrum crawling model, the time identification model is used for implementing framing of data meeting a time threshold in the network base station based on the last data crawling time, and the pattern spectrum crawling model is used for mining corresponding kyoto pattern spectrum data in the framed data.
In this embodiment, the dssd_acceptance_v3_coco model adopts a DSSD target detection algorithm, the acceptance_v3 deep neural network is pre-trained by using a coco data set, then the model is trained by using a previously prepared data set, various parameters in the deep neural network are finely tuned, and finally a suitable target detection model for detecting the spectral factors of the jingjingjingji pattern is obtained.
In this embodiment, the kyoto pattern spectrum classification module is configured to implement the arrangement and classification of the kyoto pattern spectrum based on the type of the kyoto pattern spectrum factor or the type and arrangement rule of the kyoto pattern spectrum factor by the multi-layer perceptron, and reject the repeated kyoto pattern spectrum data.
In this embodiment, the kyoto pattern spectrum generated by the kyoto pattern spectrum deriving module is configured with a database alone, and each of the kyoto pattern spectrum factors in the kyoto pattern spectrum carries a corresponding source mark, and the source kyoto pattern spectrum factors can be checked by clicking the mark.
The foregoing is merely a preferred embodiment of the present invention and it should be noted that modifications and adaptations to those skilled in the art may be made without departing from the principles of the present invention, which are intended to be comprehended within the scope of the present invention.
Claims (5)
1. A kyoto pattern pedigree sorting system, comprising:
the Beijing opera pattern spectrum crawler module is used for digging corresponding Beijing opera pattern spectrum data on each network base station based on a preset Beijing opera pattern spectrum crawling model to generate a Beijing opera pattern spectrum data set;
the Beijing opera pattern spectrum classification module is used for realizing the identification of the Beijing opera pattern spectrum factors in the Beijing opera pattern spectrum data set based on the Beijing opera pattern spectrum model D_acceptance_V3_coco and realizing the arrangement and classification of the Beijing opera pattern spectrum according to the identification result; the DSSD-acceptance-V3-coco model adopts a DSSD target detection algorithm, a coco data set is used for pre-training an acceptance-V3 deep neural network, then the model is trained by a previously prepared data set, various parameters in the deep neural network are finely adjusted, and finally a suitable target detection model for detecting Beijing opera pattern spectrum factors is obtained; the Beijing opera pattern spectrum classifying module is used for realizing the arrangement and classification of the Beijing opera pattern spectrum based on the type of the Beijing opera pattern spectrum factors or the type and arrangement rules of the Beijing opera pattern spectrum factors by the multi-layer perceptron, and eliminating repeated Beijing opera pattern spectrum data;
the Beijing opera pattern spectrum deriving module is used for realizing the segmentation, combination and arrangement of the Beijing opera pattern spectrum factors based on a preset template, generating a new Beijing opera pattern spectrum and expanding a Beijing opera pattern spectrum database; and the Beijing opera pattern spectrum generated by the Beijing opera pattern spectrum derivative module is independently provided with a database, each Beijing opera pattern spectrum factor in the Beijing opera pattern spectrum carries a corresponding source mark, and the source Beijing opera pattern spectrum factor can be checked by clicking the mark.
2. The system of claim 1, wherein the Beijing pattern spectrum crawling model comprises a time identification model and a pattern spectrum crawling model, the time identification model is used for realizing framing of data meeting a time threshold in the network base station based on last data crawling time, and the pattern spectrum crawling model is used for mining corresponding Beijing pattern spectrum data in the framed data.
3. The kyoto pattern pedigree sorting system of claim 1, further comprising:
and the crawling model training module is used for training and acquiring a pattern spectrum crawling model based on the recorded Beijing opera pattern spectrum factor set.
4. The kyoto pattern pedigree sorting system of claim 1, further comprising:
and the Beijing pattern spectrum query module is used for realizing the query of the Beijing pattern spectrum, supporting the query of texts, patterns, audios and videos, and feeding back query results in the form of an EXCEL table, wherein each query result comprises query source data and corresponding query results.
5. The kyoto pattern pedigree sorting system of claim 1, further comprising:
and the data positioning module is used for finding a proper position for the corresponding Beijing pattern spectrum data in the data according to the type of the Beijing pattern spectrum factors or the type and arrangement rules of the Beijing pattern spectrum factors, finding similar data points for the Beijing pattern spectrum data and establishing the relation between the Beijing pattern spectrum data and the similar data points.
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