CN117633361A - Similar policy recommendation method, system, equipment and storage medium - Google Patents
Similar policy recommendation method, system, equipment and storage medium Download PDFInfo
- Publication number
- CN117633361A CN117633361A CN202311714249.4A CN202311714249A CN117633361A CN 117633361 A CN117633361 A CN 117633361A CN 202311714249 A CN202311714249 A CN 202311714249A CN 117633361 A CN117633361 A CN 117633361A
- Authority
- CN
- China
- Prior art keywords
- text
- recommended
- policy
- important features
- cleaned
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Pending
Links
- 238000000034 method Methods 0.000 title claims abstract description 41
- 238000012216 screening Methods 0.000 claims abstract description 17
- 238000004140 cleaning Methods 0.000 claims abstract description 9
- 238000012545 processing Methods 0.000 claims description 14
- 238000004364 calculation method Methods 0.000 claims description 7
- 238000004590 computer program Methods 0.000 claims description 7
- 230000000007 visual effect Effects 0.000 claims description 6
- 238000004458 analytical method Methods 0.000 claims description 4
- 238000004422 calculation algorithm Methods 0.000 claims description 4
- 238000012546 transfer Methods 0.000 claims description 4
- 238000005406 washing Methods 0.000 claims 2
- 238000010586 diagram Methods 0.000 description 8
- 230000003287 optical effect Effects 0.000 description 3
- 238000000605 extraction Methods 0.000 description 2
- 230000003068 static effect Effects 0.000 description 2
- 230000009286 beneficial effect Effects 0.000 description 1
- 238000004891 communication Methods 0.000 description 1
- 239000004020 conductor Substances 0.000 description 1
- 238000013461 design Methods 0.000 description 1
- 238000011161 development Methods 0.000 description 1
- 230000000694 effects Effects 0.000 description 1
- 238000005516 engineering process Methods 0.000 description 1
- 238000001914 filtration Methods 0.000 description 1
- 238000005259 measurement Methods 0.000 description 1
- 230000007246 mechanism Effects 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 230000001105 regulatory effect Effects 0.000 description 1
- 239000004065 semiconductor Substances 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
Classifications
-
- Y—GENERAL TAGGING OF NEW TECHNOLOGICAL DEVELOPMENTS; GENERAL TAGGING OF CROSS-SECTIONAL TECHNOLOGIES SPANNING OVER SEVERAL SECTIONS OF THE IPC; TECHNICAL SUBJECTS COVERED BY FORMER USPC CROSS-REFERENCE ART COLLECTIONS [XRACs] AND DIGESTS
- Y02—TECHNOLOGIES OR APPLICATIONS FOR MITIGATION OR ADAPTATION AGAINST CLIMATE CHANGE
- Y02D—CLIMATE CHANGE MITIGATION TECHNOLOGIES IN INFORMATION AND COMMUNICATION TECHNOLOGIES [ICT], I.E. INFORMATION AND COMMUNICATION TECHNOLOGIES AIMING AT THE REDUCTION OF THEIR OWN ENERGY USE
- Y02D10/00—Energy efficient computing, e.g. low power processors, power management or thermal management
Landscapes
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The invention provides a similar policy recommending method, a similar policy recommending system, similar policy recommending equipment and a similar policy recommending storage medium, wherein the similar policy recommending method comprises the following steps: acquiring a text to be recommended, cleaning, storing the cleaned text to be recommended into a storage table, converting the cleaned text to be recommended into a vector form text, extracting features of the vector form text to obtain important features to be recommended, and storing the important features to be recommended into an index table; calculating the similarity between important features to be recommended and important features corresponding to the existing policies in the index table, and screening the existing policies as alternative policies according to the similarity; acquiring a cleaned text corresponding to the alternative policy from the storage table, calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and screening the cleaned text according to the repeated matching degree to be used as a recommendation result; and visually displaying the original policy text corresponding to the recommendation result. The method and the device screen the policy text through the similarity and the repeated matching degree, and ensure the accuracy of recommendation.
Description
Technical Field
The present invention relates to the field of computer technologies, and in particular, to a similar policy recommendation method, system, device, and storage medium.
Background
Policy making and regulatory compliance are one of the key activities of modern society, and government agencies, legal professionals, businesses, and citizens need to know and comply with numerous laws and regulations in time.
The similarity recommendation can recommend relevant policy information of a rule to be understood for a user to assist the user to understand, in the related art, a text similarity calculation method based on a vector space model is a common method in the similarity recommendation method, but the data volume of the policy text and the relevant information is huge, so that the automatic retrieval efficiency of the existing method or system is low, and large-scale policy information cannot be processed quickly.
By combining the analysis of the development status in the technical field, the prior art lacks a scheme for automatically filtering texts with higher similarity through an index engine and then carrying out repeated matching degree screening.
Disclosure of Invention
The present invention is directed to a similar policy recommendation method, system, device and storage medium, which aims to solve the above-mentioned problems in the prior art.
According to a first aspect of an embodiment of the present invention, there is provided a similar policy recommendation method, including:
acquiring a text to be recommended, cleaning, storing the cleaned text to be recommended into a storage table, converting the cleaned text to be recommended into a vector form text, extracting features of the vector form text to obtain important features to be recommended, and storing the important features to be recommended into an index table;
calculating the similarity between important features to be recommended and important features corresponding to the existing policies in the index table, and screening the existing policies as alternative policies according to the similarity;
acquiring a cleaned text corresponding to the alternative policy from the storage table, calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and screening the cleaned text according to the repeated matching degree to be used as a recommendation result;
and visually displaying the original policy text corresponding to the recommendation result.
According to a second aspect of an embodiment of the present invention, there is provided a similar policy recommendation system including:
the data processing module is used for acquiring the text to be recommended and cleaning, storing the cleaned text to be recommended into the storage table, converting the cleaned text to be recommended into a vector form text, extracting the characteristics of the vector form text to obtain important characteristics to be recommended, and storing the important characteristics to be recommended into the index table;
the similarity calculation module is used for calculating the similarity between the important features to be recommended and the important features corresponding to the existing policies in the index table, and screening the existing policies according to the similarity to serve as alternative policies;
the matching degree calculation module is used for acquiring the cleaned text corresponding to the alternative policy from the storage table, calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and screening the cleaned text according to the repeated matching degree to be used as a recommendation result;
and the visual display module is used for visually displaying the original policy text corresponding to the recommendation result.
According to a third aspect of an embodiment of the present invention, there is provided an electronic apparatus including: a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor, performs the steps of a similar policy recommendation method as provided by the first aspect of the present disclosure.
According to a fourth aspect of embodiments of the present invention, there is provided a computer-readable storage medium having stored thereon a program for implementing information transfer, which when executed by a processor, implements the steps of the similar policy recommendation method provided by the first aspect of the present disclosure.
The technical scheme provided by the embodiment of the invention has the following beneficial effects: screening out the existing policies with similar important features as alternative policies through the similarity, further screening out the policies with higher text repeated matching degree from the alternative policies, and secondarily screening out the policies to ensure the recommendation accuracy; and the important features corresponding to the policies are stored in the index table so as to facilitate quick searching, and the specific texts are stored in the database so as to facilitate storing a large amount of texts.
It is to be understood that both the foregoing general description and the following detailed description are exemplary and explanatory only and are not restrictive of the disclosure.
Drawings
For a clearer description of one or more embodiments of the present description or of the solutions of the prior art, the drawings that are necessary for the description of the embodiments or of the prior art will be briefly described, it being apparent that the drawings in the description that follow are only some of the embodiments described in the description, from which, for a person skilled in the art, other drawings can be obtained without inventive faculty.
FIG. 1 is a flow chart of a similar policy recommendation method according to an embodiment of the present invention;
FIG. 2 is a schematic diagram of data stream transfer according to an embodiment of the present invention;
FIG. 3 is a schematic diagram of a recommendation method framework according to an embodiment of the present invention;
FIG. 4 is a schematic diagram of a similar policy recommendation system according to an embodiment of the present invention;
fig. 5 is a schematic diagram of an electronic device according to an embodiment of the invention.
Detailed Description
In order to enable a person skilled in the art to better understand the technical solutions in one or more embodiments of the present specification, the technical solutions in one or more embodiments of the present specification will be clearly and completely described below with reference to the drawings in one or more embodiments of the present specification, and it is obvious that the described embodiments are only some embodiments of the present specification, not all embodiments. All other embodiments, which can be made by one or more embodiments of the present disclosure without inventive faculty, are intended to be within the scope of the present disclosure.
Method embodiment
According to an embodiment of the present invention, a similar policy recommendation method is provided, and fig. 1 is a flowchart of the similar policy recommendation method according to the embodiment of the present invention, as shown in fig. 1, where the similar policy recommendation method according to the embodiment of the present invention specifically includes:
in step S110, a text to be recommended is obtained and cleaned, the cleaned text to be recommended is stored in a storage table, the cleaned text to be recommended is converted into a vector form text, feature extraction is performed on the vector form text, important features to be recommended are obtained, and the important features to be recommended are stored in an index table. The method specifically comprises the following steps:
the storage table of the embodiment of the invention is a database type MySQL table, the types of the forms are various, for example, original text is stored, cleaned text is stored, recommended results are stored, after a user inputs the text to be recommended, the text to be recommended is stored in the storage table for storing the original text, the text to be recommended is obtained from the storage table, null value processing, repeated value processing and special character processing are sequentially carried out on the text to be recommended, the cleaned text to be recommended is obtained, and the cleaned text to be recommended is stored in the storage table for storing the cleaned text to be recommended.
And converting the text to be recommended after cleaning into a vector form text by using a Sentence BERT Sentence embedding model.
Extracting policy types, policy topics, policy release information and policy access amount information in the vector form text to obtain important features to be recommended corresponding to the vector form text, wherein the policy types comprise policy interpretation, project declaration, result disclosure and the like, the policy topics comprise rework and reproduction, a business environment, talent introduction and the like, the policy release information comprises information sources, release mechanisms, release dates, policy release display orders and the like, and the policy access amount information comprises total access amount, current year/month/day access amount, total browsing duration and the like.
Knowing the nature and purpose of the policy by policy type helps to provide more relevant recommendations to users according to a particular type of policy, knowing the needs and preferences of users by policy topic, determining the credibility and authority of the policy by policy release information, release date and release authority can set weights to text order the vector forms corresponding to the policy, and policy access information can more prominently present popular and popular policies to customers. In step S120, the similarity between the important features to be recommended and the important features corresponding to the existing policies in the index table is calculated, and the existing policies are filtered as alternative policies according to the similarity. The method specifically comprises the following steps:
acquiring important features of the existing policy from a pre-established index table of a search engine tool type, wherein the index table used in the embodiment is an ES index table;
and calculating cosine similarity, euclidean distance, manhattan distance, jaccard similarity and pearson correlation coefficient of the important features to be recommended and the important features corresponding to the existing policies, taking the average value of the cosine similarity, euclidean distance, manhattan distance, jaccard similarity and pearson correlation coefficient as the similarity of the important features to be recommended and the important features corresponding to the existing important features, and screening and sorting the important features before or exceeding a certain threshold value or other modes according to the similarity to obtain the alternative policies. In step S130, the cleaned text corresponding to the alternative policy is obtained from the storage table, the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy is calculated, and the cleaned text is filtered as the recommendation result according to the repeated matching degree. The method specifically comprises the following steps:
calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy through a Fuzzy matching algorithm, wherein the Fuzzy matching algorithm is specifically a Fuzzy similar distance, and the optional measurement mode of the Fuzzy similar distance comprises: edit distance rules, similarity rules based on N-gram, similarity rules based on bag of words model.
In step S140, the original policy text corresponding to the recommendation result is visually displayed. The method specifically comprises the following steps:
and generating a visual result report comprising repeated analysis and detail suggestion according to the original policy text corresponding to the recommended result.
The above technical solutions of the embodiments of the present invention are illustrated with reference to the following drawings.
Fig. 2 is a schematic diagram of data flow transfer in an embodiment of the present invention, as shown in fig. 2, showing that policy texts are primarily filtered through important features in a background ES index table, texts with high repeated matching degree with policy texts to be recommended are screened out from the filtered policy texts, recommendation results are obtained and stored in a database, and users obtain recommendation results from the database.
FIG. 3 is a schematic diagram of a recommendation method framework according to an embodiment of the present invention, and as shown in FIG. 3, a complete design framework according to an embodiment of the present invention is shown, the bottom layer shows source channels of data and technical supports related to the present invention, and the upper layers describe processing manners related to the present invention.
In summary, aiming at the problems existing in the current situation, the similar policy recommendation method of the invention is based on multiple types of policy data, the existing policies with similar important features are screened out through similarity to serve as alternative policies, the multiple similarity calculation methods are integrated to avoid deviation, the types contained in the important features can be comprehensively presented with more accurate policy recommendation, the policies with higher text repeated matching degree are further screened out from the alternative policies, and the accuracy of recommendation is ensured through secondary screening; and the important features corresponding to each policy are stored in the index table so as to be convenient for quick searching, the specific texts are stored in the database so as to be convenient for storing a large number of texts, and after the whole recommending process is finished, the original text information, the cleaned information and the important features of the texts to be recommended are stored in the corresponding index table or database, so that the information of the existing policy is expanded.
System embodiment
According to an embodiment of the present invention, there is provided a similar policy recommendation system, and fig. 4 is a schematic diagram of the similar policy recommendation system according to the embodiment of the present invention, as shown in fig. 4, the similar policy recommendation system according to the embodiment of the present invention specifically includes:
the data processing module 40 is configured to obtain a text to be recommended and clean, store the cleaned text to be recommended in the storage table, convert the cleaned text to be recommended into a vector form text, perform feature extraction on the vector form text to obtain important features to be recommended, and store the important features to be recommended in the index table, where the data processing module is specifically configured to:
and acquiring a text to be recommended, sequentially carrying out null value processing, repeated value processing and special character processing on the text to be recommended to obtain a cleaned text to be recommended, and storing the cleaned text to be recommended into a database type storage table.
The text to be recommended after cleaning is converted into text in a vector form by using a Sentence BERT model.
And extracting the policy type, the policy theme, the policy release information and the policy access amount information in the vector form text to obtain important features to be recommended corresponding to the vector form text.
The similarity calculating module 42 is configured to calculate a similarity between the important feature to be recommended and an important feature corresponding to an existing policy in the index table, and filter the existing policy according to the similarity as an alternative policy, and specifically is configured to:
acquiring important features of the existing policy from a pre-established index table of a search engine tool type;
and calculating cosine similarity, euclidean distance, manhattan distance, jacquard similarity and pearson correlation coefficient of the important features to be recommended and the important features corresponding to the existing policies, and taking the average value of the cosine similarity, euclidean distance, manhattan distance, jacquard similarity and pearson correlation coefficient as the similarity of the important features to be recommended and the corresponding existing important features.
The matching degree calculating module 44 is configured to obtain the cleaned text corresponding to the alternative policy from the storage table, calculate a repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and filter the cleaned text as a recommendation result according to the repeated matching degree, where the method is specifically configured to:
and calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy through a fuzzy matching algorithm.
The visual display module 46 is configured to visually display the original policy text corresponding to the recommendation result, and is specifically configured to:
and generating a visual result report comprising repeated analysis and detail suggestion according to the original policy text corresponding to the recommended result.
In summary, aiming at the problems existing in the current situation, the similar policy recommendation system of the invention takes various types of policy data as the basis, firstly screens out the existing policies with similar important characteristics as alternative policies through similarity, and synthesizes various similarity calculation methods to avoid deviation, wherein the types contained in the important characteristics can comprehensively present more accurate policy recommendation, and then further screens out the policies with higher text repeated matching degree from the alternative policies, and secondary screening ensures the accuracy of recommendation; and the important features corresponding to each policy are stored in the index table so as to be convenient for quick searching, the specific texts are stored in the database so as to be convenient for storing a large number of texts, and after the whole recommending process is finished, the original text information, the cleaned information and the important features of the texts to be recommended are stored in the corresponding index table or database, so that the information of the existing policy is expanded.
Electronic device embodiment
Fig. 5 is a schematic diagram of an electronic device according to an embodiment of the invention. The electronic device 500 may include at least one processor 510 and memory 520. Processor 510 may execute instructions stored in memory 520. The processor 510 is communicatively coupled to the memory 520 via a data bus. In addition to memory 520, processor 510 may be communicatively coupled with input device 530, output device 540, and communication device 550 via a data bus.
The processor 510 may be any conventional processor, such as a commercially available CPU. The processor may also include, for example, an image processor (Graphic Process Unit, GPU), a field programmable gate array (Field Programmable Gate Array, FPGA), a System On Chip (SOC), an application specific integrated Chip (Application Specific Integrated Circuit, ASIC), or a combination thereof.
The memory 520 may be implemented by any type or combination of volatile or nonvolatile memory devices such as Static Random Access Memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic or optical disk.
In the embodiment of the present disclosure, the memory 520 stores executable instructions, and the processor 510 may read the executable instructions from the memory 520 and execute the instructions to implement all or part of the steps of the similar policy recommendation method of any of the above-described exemplary embodiments.
Computer-readable storage medium embodiments
In addition to the methods and apparatus described above, exemplary embodiments of the present disclosure may also be a computer program product or a computer-readable storage medium storing the computer program product, the computer program product including computer program instructions executable by a processor to implement all or part of the steps described in the similar policy recommendation method of any of the above exemplary embodiments.
The computer program product may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, C++ or the like and conventional procedural programming languages, such as the "C" programming language or similar programming languages, and scripting languages (e.g., python). The program code may execute entirely on the user's computing device, partly on the user's device, as a stand-alone software package, partly on the user's computing device, partly on a remote computing device, or entirely on the remote computing device or server.
A computer readable storage medium may employ any combination of one or more readable media. The readable medium may be a readable signal medium or a readable storage medium. The readable storage medium may include, for example, but is not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or a combination of any of the foregoing. More specific examples of the readable storage medium include: a Static Random Access Memory (SRAM), an electrically erasable programmable read-only memory (EEPROM), an erasable programmable read-only memory (EPROM), a programmable read-only memory (PROM), a read-only memory (ROM), a magnetic memory, a flash memory, a magnetic or optical disk, or any suitable combination of the foregoing having one or more electrical conductors.
Finally, it should be noted that: the above embodiments are only for illustrating the technical solution of the present invention, and not for limiting the same; although the invention has been described in detail with reference to the foregoing embodiments, it will be understood by those of ordinary skill in the art that: the technical scheme described in the foregoing embodiments can be modified or some or all of the technical features thereof can be replaced by equivalents; such modifications and substitutions do not depart from the spirit of the invention.
Claims (10)
1. A similar policy recommendation method, comprising:
acquiring a text to be recommended, cleaning, storing the cleaned text to be recommended into a storage table, converting the cleaned text to be recommended into a vector form text, extracting features of the vector form text to obtain important features to be recommended, and storing the important features to be recommended into an index table;
calculating the similarity between the important features to be recommended and important features corresponding to the existing policies in the index table, and screening the existing policies as alternative policies according to the similarity;
acquiring a cleaned text corresponding to the alternative policy from the storage table, calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and screening the cleaned text according to the repeated matching degree to be used as a recommendation result;
and visually displaying the original policy text corresponding to the recommendation result.
2. The method of claim 1, wherein the obtaining the text to be recommended and cleaning, and storing the cleaned text to be recommended in the storage table specifically comprises:
and acquiring a text to be recommended, sequentially carrying out null value processing, repeated value processing and special character processing on the text to be recommended to obtain a cleaned text to be recommended, and storing the cleaned text to be recommended into a database type storage table.
3. The method of claim 1, wherein converting the cleaned text to be recommended into vector form text specifically comprises: and converting the text to be recommended after cleaning into a vector form text by using a Sentence BERT Sentence embedding model.
4. The method of claim 1, wherein the extracting features of the vector form text to obtain important features to be recommended specifically includes:
and extracting the policy type, the policy theme, the policy release information and the policy access amount information in the vector form text to obtain important features to be recommended corresponding to the vector form text.
5. The method of claim 1, wherein the calculating the similarity between the important features to be recommended and the important features corresponding to the existing policies in the index table specifically comprises:
acquiring important features of the existing policy from a pre-established index table of a search engine tool type;
and calculating cosine similarity, euclidean distance, manhattan distance, jacquard similarity and pearson correlation coefficient of the important features to be recommended and the important features corresponding to the existing policies, and taking average values of the cosine similarity, euclidean distance, manhattan distance, jacquard similarity and pearson correlation coefficient as the similarity of the important features to be recommended and the corresponding existing important features.
6. The method of claim 1, wherein calculating the repeated matching degree of the text to be recommended after washing and the text after washing corresponding to the alternative policy specifically comprises:
and calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy through a fuzzy matching algorithm.
7. The method of claim 1, wherein the visually displaying the original policy text corresponding to the recommendation result specifically includes: and generating a visual result report comprising repeated analysis and detail suggestion according to the original policy text corresponding to the recommended result.
8. A similar policy recommendation system, comprising:
the data processing module is used for acquiring a text to be recommended and cleaning, storing the cleaned text to be recommended into a storage table, converting the cleaned text to be recommended into a vector form text, extracting features of the vector form text to obtain important features to be recommended, and storing the important features to be recommended into an index table;
the similarity calculation module is used for calculating the similarity between the important features to be recommended and important features corresponding to the existing policies in the index table, and screening the existing policies according to the similarity to serve as alternative policies;
the matching degree calculation module is used for acquiring the cleaned text corresponding to the alternative policy from the storage table, calculating the repeated matching degree of the cleaned text to be recommended and the cleaned text corresponding to the alternative policy, and screening the cleaned text according to the repeated matching degree to be used as a recommendation result;
and the visual display module is used for visually displaying the original policy text corresponding to the recommendation result.
9. An electronic device, comprising: a memory, a processor and a computer program stored on the memory and executable on the processor, which when executed by the processor, implements the steps of the similar policy recommendation method as defined in any of claims 1 to 7.
10. A computer-readable storage medium, wherein a program for realizing information transfer is stored on the computer-readable storage medium, which when executed by a processor, realizes the steps of the similar policy recommendation method according to any one of claims 1 to 7.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311714249.4A CN117633361A (en) | 2023-12-13 | 2023-12-13 | Similar policy recommendation method, system, equipment and storage medium |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN202311714249.4A CN117633361A (en) | 2023-12-13 | 2023-12-13 | Similar policy recommendation method, system, equipment and storage medium |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN117633361A true CN117633361A (en) | 2024-03-01 |
Family
ID=90023355
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN202311714249.4A Pending CN117633361A (en) | 2023-12-13 | 2023-12-13 | Similar policy recommendation method, system, equipment and storage medium |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN117633361A (en) |
-
2023
- 2023-12-13 CN CN202311714249.4A patent/CN117633361A/en active Pending
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US11188537B2 (en) | Data processing | |
| US20190042628A1 (en) | Similar document identification using artificial intelligence | |
| Hunter et al. | Assessing the quality and trustworthiness of citizen science data | |
| CN109508420B (en) | Method and device for cleaning attributes of knowledge graph | |
| JP5647508B2 (en) | System and method for identifying short text communication topics | |
| US8868609B2 (en) | Tagging method and apparatus based on structured data set | |
| CN111753198A (en) | Information recommendation method and device, electronic equipment and readable storage medium | |
| CN111475612A (en) | Construction method, device and equipment of early warning event map and storage medium | |
| US11232134B2 (en) | Customized visualization based intelligence augmentation | |
| US20200097881A1 (en) | Data distillery for signal detection | |
| CN114462616A (en) | Machine learning model for preventing sensitive data from being disclosed online | |
| CN111259160A (en) | Knowledge graph construction method, device, equipment and storage medium | |
| CN106708965A (en) | Data processing method and apparatus | |
| US8775336B2 (en) | Interactive interface for object search | |
| WO2014201833A1 (en) | Method and device for processing data | |
| US8140464B2 (en) | Hypothesis analysis methods, hypothesis analysis devices, and articles of manufacture | |
| CN116541752A (en) | Metadata management method, device, computer equipment and storage medium | |
| JP6868576B2 (en) | Event presentation system and event presentation device | |
| KR101742041B1 (en) | an apparatus for protecting private information, a method of protecting private information, and a storage medium for storing a program protecting private information | |
| WO2022051996A1 (en) | Method and apparatus for constructing knowledge graph | |
| US20150235138A1 (en) | System, method, and storage medium for generating hypotheses in data sets | |
| CN113159738A (en) | Business item processing method and device, electronic equipment and storage medium | |
| TWI575391B (en) | Social data filtering system, method and non-transitory computer readable storage medium of the same | |
| CN112163098A (en) | Knowledge graph creating method and device, storage medium and server | |
| CN115544214B (en) | Event processing method, device and computer readable storage medium |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination |