CN113609350A - Competitive product enterprise retrieval method, system, storage medium and information processing terminal - Google Patents
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Abstract
The invention belongs to the technical field of data processing, and discloses a searching method, a system, a storage medium and an information processing terminal for a competitive product enterprise, wherein the searching method comprises the steps of comparing and calculating the operating range and comparing and calculating the technical strength; comparing the flow of people; comparing service revenue; storing the original features and the cleaned compressed features, and acquiring dimensional features of the query enterprise; performing comparison recall operation on all dimension characteristics in parallel, performing result fusion on all dimension characteristic recall results and selecting required results; acquiring specific explanation data corresponding to the recalling company by using the selected required result; comparing the obtained operation range with the calculated data to generate a specific explanation; and integrating the specific explanation generated by each dimension feature. The invention has comprehensive evaluation dimension and can be continuously and transversely expanded; the problem of competitive product calculation of incomplete information of medium and small enterprises is solved. The calculation result has high interpretability. The calculation emphasis can be adjusted according to the requirements.
Description
Technical Field
The invention belongs to the technical field of data processing, and particularly relates to a searching method, a searching system, a storage medium and an information processing terminal for a competitive product enterprise.
Background
At present, the best method for knowing an enterprise is to know the competitive product enterprises, and the industrial scale, the enterprise strength, the social influence and the like of the enterprise in the industry can be obtained through comparison with the competitive product enterprises.
However, most of current recall ways of competitive product enterprises are structured information generated through annual reports, stock quotations or bid information of the enterprises, and then through an information extraction technology, the generation process of the list is still mostly manual participation, so the data volume is relatively limited, for small and medium enterprises, the information which can be obtained is very limited, and information such as the stock quotations or the annual reports of the enterprises cannot be obtained, so that the competitive product enterprise information cannot be obtained, which is also the reason why most of financial institutions only do the data of listed companies, and the calculation of competitive products of the small and medium enterprises is also indispensable for serving more comprehensive business scenes.
Through the above analysis, the problems and defects of the prior art are as follows:
the existing enterprises have incomplete data and do not disclose the calculation of the competitive product enterprises of the competitive product information.
Disclosure of Invention
Aiming at the problems in the prior art, the invention provides a searching method, a searching system, a storage medium and an information processing terminal for a competitive product enterprise.
The invention is realized in this way, a searching method for competitive product enterprises, which comprises the following steps:
acquiring dimensional characteristics of an inquiry enterprise; performing comparison recall operation on the dimensional features in parallel; performing result fusion on the dimensional feature recall results and selecting a required result;
acquiring specific explanation data corresponding to the recalling company by using the selected required result; comparing the obtained operation range with the calculated data to generate a specific explanation; and integrating the specific explanation generated by each dimension feature.
Further, before acquiring and querying the dimensional features of the enterprise, the following steps are required:
(1) comparing and calculating the operation range;
(2) comparing and calculating the technical strength;
(3) comparing the flow of people;
(4) comparing service revenue;
(5) and so on;
(6) and storing the original characteristics and the cleaned compressed characteristics.
Further, the step (1) specifically includes:
collecting enterprise operation range information;
cleaning and characteristic processing are carried out on the operation range, and the main business direction is extracted;
comparing the operating ranges, and calculating the operating range overlapping rate;
overlapping business scopes are extracted and normalized.
The step (2) specifically comprises:
collect enterprise prior art characteristics, include: patents, treatises, public opinions, official nets;
cleaning the original data and extracting the technical relevant characteristics of the original data, wherein the technical relevant characteristics comprise: main technical direction, comprehensive technical direction and industry ranking;
comparing the technical strength;
and extracting high-technology competition points.
The step (3) specifically comprises:
collecting all personnel related data of a business, comprising: public opinion reports, business changes, literature output, bid publicity;
carrying out data cleaning on the collected information, and carrying out name disambiguation processing on the total data;
counting and comparing the talent competition conditions of the enterprises and the social influence of related personnel;
the foundation is the talents in competition and the social influence and the outcome yield of the talents.
The step (4) specifically comprises:
collecting annual newspaper information, financial newspaper information and financial public opinion related information of enterprises;
cleaning and event extraction are carried out on the original data, and the original data are related to specific industrial products;
comparing the competition conditions of business revenue of enterprises under specific industrial products;
specific industry revenue data is used as a support point for interpretation.
Another object of the present invention is to provide a search system for an auction product enterprise, comprising:
the operation range comparison calculation module is used for comparing operation ranges and calculating the operation range overlapping rate;
the technical strength comparison calculation module is used for cleaning the original data, extracting technical relevant characteristics of the original data and comparing technical strength;
the personnel flow comparison module is used for carrying out data cleaning on the collected information and carrying out name disambiguation processing on the total data;
the service revenue comparison module is used for cleaning and extracting events from the original data and associating the events with specific industrial products;
the compressed feature storage module is used for storing the original features and the cleaned compressed features;
the competitive product retrieval module is used for acquiring all dimensional characteristics of the query enterprise and performing comparison recall operation on all dimensions in parallel; the system is also used for carrying out result fusion on the recall result of each dimension;
the extended interpretation module is used for acquiring specific interpretation data corresponding to the recalling company; for integrating the interpretation of the dimensions.
Another object of the present invention is to provide a computer device, which includes a memory and a processor, wherein the memory stores a computer program, and the computer program, when executed by the processor, causes the processor to execute the competition enterprise retrieval method.
Another object of the present invention is to provide a computer-readable storage medium, which stores a computer program, and when the computer program is executed by a processor, the processor executes the competitive product enterprise retrieval method.
Another object of the present invention is to provide an information data processing terminal for acquiring a competitive products enterprise, wherein the information data processing terminal for acquiring a competitive products enterprise is used to implement the search method for the competitive products enterprise.
By combining all the technical schemes, the invention has the advantages and positive effects that:
the invention has comprehensive evaluation dimension and can be continuously and transversely expanded; the problem of competitive product calculation of incomplete information of medium and small enterprises is solved. The calculation result has high interpretability. The calculation emphasis can be adjusted according to the requirements.
Technical effect or experimental effect of comparison.
Drawings
In order to more clearly illustrate the technical solutions of the embodiments of the present application, the drawings needed to be used in the embodiments of the present application will be briefly described below, and it is obvious that the drawings described below are only some embodiments of the present application, and it is obvious for those skilled in the art that other drawings can be obtained from the drawings without creative efforts.
Fig. 1 is a schematic diagram of an auction enterprise retrieval system according to an embodiment of the present invention.
In fig. 1: 1. the operation range comparison calculation module; 2. a technical strength comparison calculation module; 3. a personnel flow comparison module; 4. a service revenue comparison module; 5. a compression feature storage module; 6. a bid retrieval module; 7. and expanding the interpretation module.
Figure 2 is a schematic diagram of a competitive enterprise search provided by an embodiment of the present invention,
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, the present invention is further described in detail with reference to the following embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the invention and are not intended to limit the invention.
The technical characteristics of the invention relate to the following aspects, and the following specific analysis is carried out:
the technical scheme provided by the invention is not used for evaluating the enterprise, but used for searching the competitive products of the enterprise, and the two methods have great difference. The enterprise evaluation focuses on scoring a single enterprise, the quality competition check is to compare whether two enterprises have competition relations in all evaluation directions and the competition strength, and unilateral scoring is not performed, so that an evaluation formula manually made does not exist, and the two enterprises have great difference in input items and intentions.
In the competition evaluation process of two enterprises, different characterization technical means and evaluation schemes are adopted in different evaluation directions, and both the technical means and the evaluation schemes are technical means. The following is a detailed description:
(1) when comparing the business operation range, the original business operation range is a long text, and the comparison cannot be performed, so that the numeralization is needed. The business scope text needs to be: the method comprises the technical means of word segmentation, cleaning, keyword extraction, keyword standardization, word weight calculation, word vectorization, word vector fusion and the like. The word weight calculation is obtained by adopting mathematical statistics analysis, and objectively reflects real data rules, rather than manual typing. The word vector quantization is an unsupervised word2vec model, does not mix with prior artificial features, and can feed back a relative objective inter-word relation. The cosine similarity is an objective formula and cannot be generalized with artificial rules, and the feature generation process is also a technical means and is not an artificial rule.
(2) When contrast personnel flow, personnel disambiguation needs to be performed on the related data of the total personnel in advance, the specific technical scheme can be briefly stated that model training is performed on a labeled data set by using a regression forest model, after the model training is finished, the total data is predicted, namely, the homonymy disambiguation is performed on the total data, the model type is a machine learning model, the personnel disambiguation is performed on the basis of supervised learning training instead of manual design rules, the model is trained on objective real data, and natural rules can be fed back. Although the final comparison process is only to see if there is a flow of people between two enterprises, the data processing process behind them cannot be abraded through a great number of technical means.
(3) When comparing enterprise revenues (enterprise additional assessment items on the market), the original enterprise financial reports are mostly in PDF format, need to adopt OCR technique to discern it earlier, then standardize once more, to information after the standardization, also not directly write the formula and just can directly compare, the product revenues of every enterprise writes the mode and product expression and all has the difference, consequently still need standardize the product name to adopt corresponding algorithm to merge in the concrete industry. Such as: OCR recognition, product name labeling, industrialization and the like are all technical means, and the problem can be solved without manually writing rules.
Aiming at the problems in the prior art, the invention provides a searching method for a competitive product enterprise, which is described in detail below with reference to the accompanying drawings.
As shown in fig. 1, the auction enterprise retrieval system provided by the embodiment of the present invention includes:
the operation range comparison calculation module 1 is used for comparing operation ranges and calculating the operation range overlapping rate;
the technical strength comparison calculation module 2 is used for cleaning the original data, extracting technical relevant characteristics of the original data and comparing technical strength;
the personnel flow comparison module 3 is used for carrying out data cleaning on the collected information and carrying out name disambiguation processing on the total data;
the service revenue comparison module 4 is used for cleaning and event extraction of the original data and associating the original data with specific industrial products;
a compression characteristic storage module 5 for storing the original characteristics and the cleaned compression characteristics;
the bid retrieval module 6 is used for acquiring all dimension characteristics of the query enterprise and performing comparison recall operation on all dimensions in parallel; the system is also used for carrying out result fusion on the recall result of each dimension;
the extended interpretation module 7 is used for acquiring specific interpretation data corresponding to the recalling company; for integrating the interpretation of the dimensions.
As shown in fig. 2, the overall calculation architecture is composed of a plurality of sub-modules with the same architecture, different sub-modules respectively calculate different dimensional characteristics and compare the similarity degree in the dimension, and finally the sub-modules not only need to output similarity values, but also form specific interpretable similarity points, and each model is independent and does not conflict with each other, so that the mining and the lateral expansion of the calculation dimension can be continuously performed.
Calculating each dimension in a parallel mode, collecting similarity output of each sub-module for comprehensive sequencing, and generating an interpretation text by using similar points with interpretability.
In each submodule, specific data distribution aiming at the dimension to be processed is adopted to carry out specific feature extraction, and the feature comparison process only carries out calculation on the feature to be processed.
In the specific implementation process, although the similarity is obtained through calculation based on the similarity, in order to make the similarity more readable, standardization or text generation processing is often needed, in the actual operation process, the original features are characterized and persistently stored, at this time, all information is contained in the features, but the similarity is not urgently generated, the similarity is preferentially calculated through parallel similarity calculation, and result recall operation is performed according to the comprehensive similarity.
Sequencing according to the comprehensive similarity, selecting a TopN result, recalling the complete characteristics of TopN, and then performing the generation process of the similar points, wherein the calculation process of the similar points is similar to the characteristic extraction mode, but text cleaning and standardization processes are added, so that the similar points are more readable.
Meanwhile, based on business requirements, the sub-modules can be used independently, and can be combined optionally according to requirements, so that more scenes can be met.
The technical solution of the present invention is further described below with reference to specific examples.
Examples
In the using process, the specific execution steps are as follows:
1. a first module: and (3) comparing and calculating the operation range:
1.1 collecting enterprise operation range information;
1.2, cleaning and characteristic processing are carried out on the operation range, and the main business direction is extracted;
1.3 comparing the operating ranges, and calculating the operating range overlapping rate;
1.4 extracting and standardizing overlapping business ranges.
2. And a second module: and (3) comparing and calculating the technical strength:
2.1 collecting the prior art characteristics of enterprises, such as: patents, treatises, public opinions, official nets, etc.;
2.2, cleaning the original data and extracting the technical relevant characteristics of the original data, such as: main technical direction, comprehensive technical direction, industry ranking and the like;
2.3 comparing the technical strength;
2.4 extracting high technology competition points.
3. And a third module: comparison of flow of people:
3.1 collect all personnel related data of the enterprise, such as: public opinion reports, business changes, literature output, bid public notices, etc.;
3.2, cleaning the collected information and carrying out name disambiguation treatment on the total data;
3.3 counting and comparing the talent competition conditions of the enterprises and the social influence of related personnel;
3.4 the foundation of the competition talents and the social influence and outcome yield of the talents.
4. And a module IV: and (3) service revenue comparison:
4.1 collecting related information such as annual newspaper information, financial public opinion and the like of the enterprise;
4.2, cleaning and event extraction are carried out on the original data, and the original data are related to specific industrial products;
4.3 comparing the competition conditions of business revenue of enterprises under specific industrial products;
4.4 specific industry revenue data is used as a support point for interpretation.
5. And so on, including but not limited to the above dimensions.
6. And storing the original characteristics and the cleaned compressed characteristics.
7. Searching for the competitive products:
7.1 acquiring dimensional characteristics of the query enterprise;
7.2 performing comparison recall operation on all dimensions in parallel;
7.3, result fusion is carried out on the recall result of each dimension;
7.4 pick the desired result.
8. Extended interpretation
8.1 acquiring specific explanation data corresponding to the recalling company;
8.2 generating specific explanations according to the above 1.4, 2.4, 3.4, 4.4;
8.3 integrate the interpretation of the dimensions.
Demonstration section (concrete examples/experiments/simulation/pharmacological analysis/positive experimental data capable of demonstrating the inventive aspects of the invention, etc.)
In the description of the present invention, "a plurality" means two or more unless otherwise specified; the terms "upper", "lower", "left", "right", "inner", "outer", "front", "rear", "head", "tail", and the like, indicate orientations or positional relationships based on the orientations or positional relationships shown in the drawings, are only for convenience in describing and simplifying the description, and do not indicate or imply that the device or element referred to must have a particular orientation, be constructed in a particular orientation, and be operated, and thus, should not be construed as limiting the invention. Furthermore, the terms "first," "second," "third," and the like are used for descriptive purposes only and are not to be construed as indicating or implying relative importance.
It should be noted that the embodiments of the present invention can be realized by hardware, software, or a combination of software and hardware. The hardware portion may be implemented using dedicated logic; the software portions may be stored in a memory and executed by a suitable instruction execution system, such as a microprocessor or specially designed hardware. Those skilled in the art will appreciate that the apparatus and methods described above may be implemented using computer executable instructions and/or embodied in processor control code, such code being provided on a carrier medium such as a disk, CD-or DVD-ROM, programmable memory such as read only memory (firmware), or a data carrier such as an optical or electronic signal carrier, for example. The apparatus and its modules of the present invention may be implemented by hardware circuits such as very large scale integrated circuits or gate arrays, semiconductors such as logic chips, transistors, or programmable hardware devices such as field programmable gate arrays, programmable logic devices, etc., or by software executed by various types of processors, or by a combination of hardware circuits and software, e.g., firmware.
The above description is only for the purpose of illustrating the present invention and the appended claims are not to be construed as limiting the scope of the invention, which is intended to cover all modifications, equivalents and improvements that are within the spirit and scope of the invention as defined by the appended claims.
Claims (10)
1. An auction product enterprise retrieval system, the auction product enterprise retrieval system comprising:
the operation range comparison calculation module is used for comparing operation ranges and calculating the operation range overlapping rate;
the technical strength comparison calculation module is used for cleaning the original data, extracting technical relevant characteristics of the original data and comparing technical strength;
the personnel flow comparison module is used for carrying out data cleaning on the collected information and carrying out name disambiguation processing on the total data;
the service revenue comparison module is used for cleaning and extracting events from the original data and associating the events with specific industrial products;
the compressed feature storage module is used for storing the original features and the cleaned compressed features;
the competitive product retrieval module is used for acquiring all dimensional characteristics of the query enterprise and performing comparison recall operation on all dimensions in parallel; the system is also used for carrying out result fusion on the recall result of each dimension;
the extended interpretation module is used for acquiring specific interpretation data corresponding to the recalling company; for integrating the interpretation of the dimensions.
2. A bid enterprise retrieval method for executing the bid enterprise retrieval system of claim 1, wherein the bid enterprise retrieval method comprises: acquiring dimensional characteristics of an inquiry enterprise; performing comparison recall operation on the dimensional features in parallel;
performing result fusion on the dimensional feature recall results and selecting a required result;
acquiring specific explanation data corresponding to the recalling company by using the selected required result; comparing the obtained operation range with the calculated data to generate a specific explanation; and integrating the specific explanation generated by each dimension feature.
3. The method of claim 2, wherein the obtaining of dimensional features of the query enterprise is preceded by:
(1) comparing and calculating the operation range;
(2) comparing and calculating the technical strength;
(3) comparing the flow of people;
(4) comparing service revenue;
(5) repeating (1) - (4);
(6) storing the original features and the cleaned compressed features.
4. The method for searching for a competitive product enterprise as claimed in claim 3, wherein the step (1) specifically comprises:
collecting enterprise operation range information;
cleaning and characteristic processing are carried out on the operation range, and the main business direction is extracted;
comparing the operating ranges, and calculating the operating range overlapping rate;
overlapping business scopes are extracted and normalized.
5. The method for searching for a competitive product enterprise as claimed in claim 3, wherein the step (2) specifically includes:
collect enterprise prior art characteristics, include: patents, treatises, public opinions, official nets;
cleaning the original data and extracting the technical relevant characteristics of the original data, wherein the technical relevant characteristics comprise: technical direction, comprehensive technical direction and industry ranking;
comparing the technical strength;
and extracting high-technology competition points.
6. The method for searching for a competitive product enterprise as claimed in claim 3, wherein the step (3) specifically comprises:
collecting all personnel related data of a business, comprising: public opinion reports, business changes, literature output, bid publicity;
carrying out data cleaning on the collected information, and carrying out name disambiguation processing on the total data;
counting and comparing the talent competition conditions of the enterprises and the social influence of related personnel;
the foundation is the talents in competition and the social influence and the outcome yield of the talents.
7. The method for searching for a competitive product enterprise as claimed in claim 3, wherein the step (4) specifically comprises:
collecting annual newspaper information, financial newspaper information and financial public opinion related information of enterprises;
cleaning and event extraction are carried out on the original data, and the original data are related to specific industrial products;
comparing the competition conditions of business revenue of enterprises under specific industrial products;
specific industry revenue data is used as a support point for interpretation.
8. A computer device comprising a memory and a processor, the memory storing a computer program that, when executed by the processor, causes the processor to perform the auction enterprise retrieval method of any one of claims 2-7.
9. A computer-readable storage medium storing a computer program which, when executed by a processor, causes the processor to execute the auction product enterprise retrieval method of any one of claims 2 to 7.
10. An information data processing terminal for obtaining competitive product enterprises, which is characterized in that the information data processing terminal for obtaining competitive product enterprises is used for realizing the search method of the competitive product enterprises according to any one of claims 2 to 7.
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| US9910899B1 (en) * | 2014-09-03 | 2018-03-06 | State Farm Mutual Automobile Insurance Company | Systems and methods for electronically mining intellectual property |
| CN107330819A (en) * | 2017-06-29 | 2017-11-07 | 朱峰 | A kind of intellectual property intelligent comparison analysis system |
| CN110750525A (en) * | 2019-10-11 | 2020-02-04 | 厦门谷道集团有限公司 | Custom obtaining method, system and equipment based on customs big data and Google search |
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