CN110750707A - Keyword recommendation method and device and electronic equipment - Google Patents
Keyword recommendation method and device and electronic equipment Download PDFInfo
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Abstract
The embodiment of the invention discloses a keyword recommendation method, a keyword recommendation device and electronic equipment. One embodiment of the method comprises: in response to the fact that the obtained current operation of the user is a preset operation, determining text information corresponding to the preset operation; searching a text keyword corresponding to the text information from a preset database, and storing the text information and the text keyword in the preset database in an associated manner; determining at least one recommended keyword based on the text keywords; and displaying the recommendation keywords. Because at least one recommended keyword is determined based on the text keyword of the text information corresponding to the current preset operation of the user, the recommended keyword is closely related to the information browsed by the user in real time. The recommended keywords are extended from the text information content corresponding to the current preset operation of the user. The user can selectively trigger the recommended keywords to quickly acquire the extended information of the text information corresponding to the current preset operation, so that the user experience can be improved.
Description
Technical Field
The invention relates to the technical field of internet, in particular to a keyword recommendation method and device and electronic equipment.
Background
With the continuous development of internet technology, the amount of internet pushed information is also increasing. When information is pushed to a user, personalized recommendation technology is generally used to select information matching with the interests of the user from a large amount of information and send the information to user terminal equipment.
In the current personalized recommendation technology, a plurality of pieces of information related to information historically browsed by a user are generally recommended to the user according to the information historically browsed by the user.
But the information pushed to the user, determined from the historical browsing information, may not match the information currently being browsed by the user.
Disclosure of Invention
The embodiment of the invention provides a keyword recommendation method, a keyword recommendation device and electronic equipment, and aims to solve the technical problems in the background technology.
In a first aspect, the present invention provides a keyword recommendation method, including: in response to the fact that the obtained current operation of the user is a preset operation, determining text information corresponding to the preset operation; searching a text keyword corresponding to the text information from a preset database, and storing the text information and the text keyword in the preset database in an associated manner; at least one recommended keyword is determined based on the text keywords.
Optionally, before searching for the text keyword corresponding to the text information from the preset database, the method further includes: acquiring a plurality of text messages; respectively determining text keywords corresponding to each text message; and associating and storing each text message with the text key words of the text message in a preset database.
Optionally, the determining at least one recommended keyword based on the text keyword includes: at least one recommended keyword is determined based on the incidence relation between the pre-established text keyword and a plurality of words extracted from the internet in advance.
Optionally, the determining at least one recommended keyword based on the text keyword includes: and determining recommended keywords based on the similarity between the text keywords and a plurality of words extracted from the Internet in advance.
Optionally, the method further comprises: pushing the recommended keywords, and responding to the acquired triggering operation of the user on the recommended keywords; determining a plurality of recommendation information associated with the recommendation keyword; and pushing the recommendation information associated with the recommendation keywords.
In a second aspect, the present invention provides a keyword recommendation apparatus, including: the first determining module is configured to determine text information corresponding to a preset operation in response to the fact that the obtained current operation of the user is the preset operation; the searching module is configured for searching a text keyword corresponding to the text information from a preset database, and the text information and the text keyword are stored in the preset database in an associated manner; a second determination module configured to determine at least one recommended keyword based on the text keyword.
Optionally, the apparatus further includes a keyword obtaining module, where the keyword obtaining module is configured to: before searching for the text keywords corresponding to the text information from the preset database, acquiring a plurality of text information, respectively determining the text keywords corresponding to each text information, and storing each text information and the text keywords of the text information in the preset database in an associated manner.
Optionally, the second determining module is further configured to: and determining the recommended keywords based on the pre-established incidence relation between the text keywords and a plurality of words extracted from the Internet in advance.
Optionally, the second determining module is further configured to: and determining recommended keywords based on the similarity between the text keywords and a plurality of words extracted from the Internet in advance.
Optionally, the device further includes a pushing module configured to push the recommended keyword and respond to the trigger operation of the obtained user on the recommended keyword; determining a plurality of recommendation information associated with the recommendation keyword; and pushing the recommendation information associated with the recommendation keywords.
In a third aspect, the present invention provides an electronic device, comprising: one or more processors; the storage device is used for storing one or more programs, and when the one or more programs are executed by the one or more processors, the one or more processors implement the steps of any one of the keyword recommendation methods.
In a fourth aspect, the present invention provides a computer readable medium, on which a computer program is stored, which when executed by a processor, performs the steps of any of the keyword recommendation methods described above.
According to the keyword recommendation method, the keyword recommendation device and the electronic equipment provided by the embodiment of the invention, at least one recommended keyword is determined based on the text keyword of the text information corresponding to the current preset operation of the user, so that the recommended keyword is closely related to the information browsed by the user in real time. The recommended keywords are extended from the text information content corresponding to the current preset operation of the user. The user can selectively trigger the recommended keywords to quickly acquire the extended information of the text information corresponding to the current preset operation, so that the user experience can be improved.
Drawings
The drawings are included to provide a better understanding of the invention and are not to be construed as unduly limiting the invention. Wherein:
FIG. 1 is a flow diagram of one embodiment of a keyword recommendation method in accordance with the present invention;
FIG. 2 is a flow diagram of yet another embodiment of a keyword recommendation method in accordance with the present invention;
FIG. 3 is a schematic diagram illustrating an embodiment of a keyword recommendation apparatus according to the present invention;
FIG. 4 is an exemplary system architecture diagram in which embodiments of the present invention may be employed;
fig. 5 is a schematic diagram of a basic structure of an electronic device provided according to an embodiment of the present invention.
Detailed Description
Exemplary embodiments of the invention are described below with reference to the accompanying drawings, in which various details of embodiments of the invention are included to assist understanding. They should be considered as merely exemplary. It will therefore be appreciated by those of ordinary skill in the art that various changes and modifications may be made to the embodiments described herein without departing from the scope and spirit of the invention.
It should be noted that the embodiments and features of the embodiments may be combined with each other without conflict.
Referring to fig. 1, fig. 1 illustrates a flow of an embodiment of a keyword recommendation method according to the present invention. The keyword recommendation method shown in fig. 1 includes the following steps:
Typically, a plurality of pieces of information may be presented in the screen of the user terminal device. The user can perform various operations on the screen of the terminal device to browse information. The various operations by the user may be, for example, clicking, touching, sliding a window, and the like. The terminal equipment can receive and detect various operations of the user and return corresponding information to the operations of the user.
In this embodiment, the preset operation may be, for example, one of the following: click operation, touch operation, sliding window operation, and the like. Through the preset operation, the user selects a piece of information displayed in the screen of the terminal equipment to browse.
The terminal equipment can monitor whether the operation executed by the user on the screen is a preset operation or not in real time. Further, the text information here includes text data and the like.
And 102, searching a text keyword corresponding to the text information from a preset database, and storing the text information and the text keyword in the preset database in an associated manner.
The database may be preset at a local or remote server. And storing a plurality of pieces of text information and text keywords corresponding to each piece of text information in a database in an associated manner.
In some embodiments, before the step 102 of searching for the text keyword corresponding to the text information from the preset database, the keyword recommendation method may further include: acquiring a plurality of text messages; respectively determining text keywords corresponding to each text message; and storing each text message and the text key word of the text message in a preset database in an associated manner.
The acquiring of the plurality of text messages may include acquiring a huge amount of text messages in the internet.
The determining of the text keywords corresponding to each text message respectively, wherein for each text message, extracting the text keyword corresponding to the text message may include the following steps: firstly, word segmentation operation is carried out on the text data of the text information to obtain a plurality of word segmentation results. Then, the text keywords of the text message are determined according to the times of the occurrence of each word segmentation result in the text message. For example, a word segmentation result with a frequency of occurrence in the text information greater than a preset frequency threshold may be determined as a text keyword of the text information. It is understood that the above word segmentation results are word segmentation results after removing some words having no practical meaning, such as "of", "ground", etc.
Each word segmentation result can correspond to a name, a dynamic noun, a noun phrase and the like. It should be noted that the word segmentation method used when performing word segmentation operation on text data is a well-known technology widely studied and applied at present, and is not described herein again.
After the text keywords corresponding to each text message are obtained, each text message and the text keywords corresponding to each text message may be stored in the preset database in an associated manner.
When the database is a local database, the text keywords corresponding to the text information corresponding to the preset operation of the user can be directly searched in the local database. When the database is arranged on a remote server, the database arranged on the remote server can be remotely accessed through a network to acquire the text keywords of the text information corresponding to the preset operation of the user.
After the text keywords of the text information corresponding to the preset operation of the user are obtained in step 102, various analyses may be performed on the text keywords to determine at least one recommended keyword.
In some implementations, multiple words may be extracted in advance from the mass information of the internet. And respectively determining the similarity between the text keyword and each word in the plurality of words extracted from the Internet in advance. And then determining a recommended keyword based on the similarity between the text keyword and each word extracted from the Internet in advance. For example, at least one word extracted in advance from the internet, which has a similarity greater than a preset similarity threshold with the text keyword, may be determined as the recommended keyword. In addition, a plurality of words extracted from the internet in advance can be sorted according to the sequence of similarity from large to small, and at least one word with the sorting number smaller than a preset sequence number threshold value is determined as the recommended keyword.
The text keywords and the words extracted from the internet in advance can be nouns, dynamic nouns, noun phrases and the like.
It should be noted that the method for calculating the similarity between different words is a well-known technique widely studied and applied at present, and is not described herein again.
In some embodiments, after the step 103 obtains at least one recommended keyword, the recommended keyword may be pushed. For example, the at least one recommended keyword may be pushed to a terminal device of the user. And displaying the recommended keywords in the current display page by the terminal equipment of the user. In some application scenarios, the terminal device may be caused to display the at least one recommendation keyword at the top of its current display page through corresponding settings. Or the terminal equipment can display the at least one recommendation keyword at the bottom of the current display page through corresponding setting.
For example, when a text keyword of text information browsed by the user at the current time is a college entrance examination, the recommended keyword may be determined: "the subject of the composition of college entrance examination" and "the score line of college entrance examination in the past year" are recommended. The recommended keywords can be pushed to user terminal equipment. So as to guide the user to browse a plurality of pieces of information related to the recommended keyword by clicking the recommended keyword.
Further, after the recommendation keyword is pushed to the user terminal, the keyword recommendation method may further include: responding to the acquired trigger operation of the user on the recommended keywords; determining a plurality of recommendation information associated with the recommendation keyword; and displaying a plurality of pieces of recommendation information associated with the recommendation keywords.
That is, after the recommended keyword is shown in the display page of the terminal device, if the recommended keyword matches the current interest of the user, the user may perform a trigger operation on the recommended keyword shown on the terminal screen, where the trigger operation may be, for example, clicking, touching, hovering, or the like.
After the user performs the triggering operation on the recommended keywords, the terminal device monitors the triggering operation of the user. The server may obtain the trigger operation of the user. In response to the trigger operation of the user on the recommendation keyword is acquired, a plurality of recommendation information associated with the recommendation keyword can be determined from the background. In some application scenarios, recommendation information with a recommendation keyword as a keyword can be searched from the internet. In other application scenarios, the recommendation information associated with the recommendation keyword may be stored in a local or remote database in advance. When the recommendation keywords triggered by the user are acquired, recommendation information associated with the recommendation keywords can be determined from the database. The recommendation information may be sent to a terminal device, so that the terminal device displays the plurality of recommendation information.
When the user executes the trigger operation on the displayed recommendation keywords, a plurality of pieces of recommendation information associated with the recommendation keywords can be continuously displayed to the user for the user to browse. Therefore, the user can obtain a large amount of information matched with the interest of the user at the current moment in a short time. The user experience can be further improved.
According to the keyword recommendation method, the keyword recommendation device and the electronic equipment provided by the embodiment of the invention, at least one recommended keyword is determined based on the text keyword of the text information corresponding to the current preset operation of the user, so that the recommended keyword is closely related to the information browsed by the user in real time. The recommended keywords are extended from the text information content corresponding to the current preset operation of the user. The user can selectively trigger the recommended keywords to quickly acquire the extended information of the text information corresponding to the current preset operation, so that the user experience can be improved.
With further reference to FIG. 2, a flow diagram of yet another embodiment of a keyword recommendation method is shown. As shown in fig. 2, the flow of the keyword recommendation method includes the following steps:
Step 201 is the same as step 101 in the embodiment shown in fig. 1, and is not described herein again.
Step 202 is the same as step 102 in the embodiment shown in fig. 1, and is not repeated here.
A plurality of words may be pre-extracted in the internet. For example, the word segmentation is performed on the text data of the text information in each internet to obtain a plurality of word segmentation results. And then, operations such as de-duplication of a plurality of word segmentation results extracted from a plurality of text messages in the Internet and the like are performed to obtain a plurality of words.
The association relationship between a plurality of words extracted in advance from the internet may be established in advance. The association relationship may be, for example, a synonymous relationship, an antisense relationship, a superordinate and subordinate relationship, a total score relationship, a class meaning relationship, or the like. The words extracted from the internet in advance and the association relationship between different words may be stored in a local or remote database.
After determining a text keyword corresponding to a current preset operation of a user, matching the text keyword with a plurality of words stored in a preset database. When the matching is successful, at least one recommended keyword can be determined in the database according to the association relation among the words.
In some application scenarios, the knowledge-graph may also be pre-established in a local or remote server. The knowledge-graph may include a plurality of entities, and relationships between different entities. Each entity may be described by a word.
Words which have direct connection relation with the text keywords can be searched in the knowledge graph to serve as recommendation keywords. And determining the recommended keywords in a pre-established knowledge graph by using a relational reasoning method. The method of the above-mentioned relationship inference may include, for example, a logical rule-based inference method, a knowledge expression-based inference method, a deep learning-based inference method, and the like.
It should be noted that the above-mentioned knowledge graph and the method for establishing the knowledge graph are well-known technologies that are widely researched and applied at present, and are not described herein again.
It should be noted that the above-mentioned inference method based on logic rules, the inference method based on knowledge expression, the inference method based on deep learning, and the like are well-known technologies that are widely researched and applied at present, and are not described herein again.
As can be seen from fig. 2, compared with the embodiment corresponding to fig. 1, the keyword recommendation method in this embodiment has a process of determining a recommended keyword from a pre-established association relationship among a plurality of words. Therefore, the scheme described in the embodiment can quickly generate the recommendation keywords, so that the user experience can be further improved.
With further reference to fig. 3, as an implementation of the method shown in the above figures, the present invention provides an embodiment of a keyword recommendation apparatus, where the embodiment of the apparatus corresponds to the embodiment of the method shown in fig. 1, and the apparatus may be specifically applied to various electronic devices.
As shown in fig. 3, the keyword recommendation apparatus of the present embodiment includes: a first determination module 301, a search module 302, and a second determination module 303. The first determining module 301 is configured to determine text information corresponding to a preset operation in response to acquiring that a current operation of a user is the preset operation; the searching module 302 is configured to search a text keyword corresponding to the text information from a preset database, wherein the text information and the text keyword are stored in the preset database in an associated manner; a second determination module 303 configured to determine at least one recommended keyword based on the text keyword.
In this embodiment, specific processes of the first determining module 301, the searching module 302, and the second determining module 303 of the keyword recommending apparatus and technical effects thereof may refer to related descriptions of step 101, step 102, and step 103 in the corresponding embodiment of fig. 1, which are not described herein again.
In some embodiments, the keyword recommendation apparatus further comprises a keyword acquisition module configured to: acquiring a plurality of text messages before searching for text keywords corresponding to the text messages from a preset database; respectively determining text keywords corresponding to each text message; and associating and storing each text message with the text key words of the text message in a preset database.
In some embodiments, the second determining module 303 is further configured to: and determining the recommended keywords based on the pre-established incidence relation between the text keywords and a plurality of words extracted from the Internet in advance.
In some embodiments, the second determining module 303 is further configured to: and determining recommended keywords based on the similarity between the text keywords and a plurality of words extracted from the Internet in advance.
In some embodiments, the keyword recommendation apparatus further includes a push module (not shown in the figure). The pushing module is configured to push the recommended keywords and respond to the acquired triggering operation of the user on the recommended keywords; determining a plurality of recommendation information associated with the recommendation keyword; and pushing a plurality of recommendation information associated with the recommendation keywords.
Referring to fig. 4, fig. 4 illustrates an exemplary system architecture to which an embodiment of a keyword recommendation method or a keyword recommendation apparatus of the present invention may be applied.
As shown in fig. 4, the system architecture may include terminal devices 401, 402, 403, a network 404 and a server 405. The network 404 serves as a medium for providing communication links between the terminal devices 401, 402, 403 and the server 405. Network 404 may include various types of connections, such as wire, wireless communication links, or fiber optic cables, to name a few.
A user may use terminal devices 401, 402, 403 to interact with a server 405 over a network 404 to receive or send messages or the like. The terminal devices 401, 402, 403 may have various client applications installed thereon, such as a web browser application, a shopping application, a search application, a news application, etc.
The terminal devices 401, 402, 403 may be various electronic devices having a display screen and supporting web browsing, including but not limited to smart phones, tablet computers, laptop portable computers, desktop computers, and the like.
The server 405 may provide various services, such as user operation information acquired from the terminal device, perform analysis processing on text information corresponding to the user operation, and determine a recommended keyword. The server 405 may feed back the determined recommended keyword to the terminal device.
It should be noted that the keyword recommendation method provided in the embodiment of the present invention is generally executed by the server 405, and accordingly, the keyword recommendation apparatus is generally disposed in the server 405.
It should be understood that the number of terminal devices, networks, and servers in fig. 4 is merely illustrative. There may be any number of terminal devices, networks, and servers, as desired for implementation.
Referring now to FIG. 5, a basic block diagram of an electronic device (server) suitable for use in implementing embodiments of the present invention is shown. The electronic device shown in fig. 5 is only an example, and should not bring any limitation to the functions and the scope of use of the embodiments of the present invention.
As shown in fig. 5, an electronic device may include one or more processors 501, storage 502. The storage device 502 is used to store one or more programs. One or more programs in storage 502 may be executed by one or more processors 501. The one or more programs, when executed by the one or more processors, enable the one or more processors to implement the above-described functions defined in the method of the present invention.
The modules described in the embodiments of the present invention may be implemented by software or hardware. The described modules may also be provided in a processor, which may be described as: a processor includes a first determination module, a lookup module, and a second determination module. The names of the modules do not form a limitation on the modules themselves in some cases, for example, the first determination module may also be described as a "module that determines text information corresponding to a preset operation".
As another aspect, the present invention also provides a computer-readable medium that may be contained in the apparatus described in the above embodiments; or may be separate and not incorporated into the device. The computer readable medium of the present invention may be a computer readable signal medium or a computer readable storage medium or any combination of the two. A computer readable storage medium may be, for example, but not limited to, an electronic, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus, or device, or any combination of the foregoing. More specific examples of the computer readable storage medium may include, but are not limited to: an electrical connection having one or more wires, a portable computer diskette, a hard disk, a Random Access Memory (RAM), a read-only memory (ROM), an erasable programmable read-only memory (EPROM or flash memory), an optical fiber, a portable compact disc read-only memory (CD-ROM), an optical storage device, a magnetic storage device, or any suitable combination of the foregoing.
The computer readable medium carries one or more programs which, when executed by the apparatus, cause the apparatus to: in response to the fact that the obtained current operation of the user is a preset operation, determining text information corresponding to the preset operation; searching a text keyword corresponding to the text information from a preset database, wherein the text information and the text keyword are stored in the preset database in an associated manner; at least one recommended keyword is determined based on the text keywords.
The above-described embodiments should not be construed as limiting the scope of the invention. Those skilled in the art will appreciate that various modifications, combinations, sub-combinations, and substitutions can occur, depending on design requirements and other factors. Any modification, equivalent replacement, and improvement made within the spirit and principle of the present invention should be included in the protection scope of the present invention.
Claims (10)
1. A keyword recommendation method is characterized by comprising the following steps:
in response to the fact that the obtained current operation of the user is a preset operation, determining text information corresponding to the preset operation;
searching a text keyword corresponding to the text information from a preset database, wherein the text information and the text keyword are stored in the preset database in an associated manner;
at least one recommended keyword is determined based on the text keywords.
2. The method according to claim 1, wherein before the searching for the text keyword corresponding to the text information from the preset database, the method further comprises:
acquiring a plurality of text messages;
respectively determining text keywords corresponding to each text message;
and associating and storing each text message with the text key words of the text message in the preset database.
3. The method of claim 1, wherein determining at least one recommended keyword based on the text keyword comprises:
and determining at least one recommended keyword based on the pre-established association relationship between the text keyword and a plurality of words extracted from the Internet in advance.
4. The method of claim 1, wherein determining at least one recommended keyword based on the text keyword comprises:
and determining recommended keywords based on the similarity between the text keywords and a plurality of words extracted from the Internet in advance.
5. The method according to any one of claims 1-4, further comprising:
push the recommended keywords, an
Responding to the acquired trigger operation of the user on the recommended keywords;
determining a plurality of recommendation information associated with the recommendation keyword;
and pushing the recommendation information associated with the recommendation keywords.
6. A keyword recommendation apparatus, comprising:
the first determining module is configured to determine text information corresponding to a preset operation in response to the fact that the obtained current operation of the user is the preset operation;
the searching module is configured to search a text keyword corresponding to the text information from a preset database, and the text information and the text keyword are stored in the preset database in an associated manner;
a second determination module configured to determine at least one recommended keyword based on the text keyword.
7. The apparatus of claim 6, further comprising a keyword acquisition module configured to:
before searching the text keywords corresponding to the text information from the preset database, acquiring a plurality of text information, respectively determining the text keywords corresponding to each text information, and storing each text information and the text keywords of the text information in the preset database in an associated manner.
8. The apparatus of claim 6, wherein the second determining module is further configured to:
and determining a recommended keyword based on the pre-established incidence relation between the text keyword and a plurality of words extracted from the Internet in advance.
9. An electronic device, comprising:
one or more processors;
a storage device for storing one or more programs,
when executed by the one or more processors, cause the one or more processors to implement the method of any one of claims 1-5.
10. A computer-readable medium, on which a computer program is stored which, when being executed by a processor, carries out the method according to any one of claims 1-5.
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Cited By (4)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111797201A (en) * | 2020-06-23 | 2020-10-20 | 中民筑友建设科技集团有限公司 | BIM (building information modeling) model acquisition method, device, equipment and computer readable storage medium |
| CN112328805A (en) * | 2020-10-29 | 2021-02-05 | 北京华云安信息技术有限公司 | Entity mapping method of vulnerability description information and database table based on NLP |
| CN112487765A (en) * | 2020-11-23 | 2021-03-12 | 建信金融科技有限责任公司 | Method and device for generating notification text |
| CN113409123A (en) * | 2021-07-01 | 2021-09-17 | 北京沃东天骏信息技术有限公司 | Information recommendation method, device, equipment and storage medium |
Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104239298A (en) * | 2013-06-06 | 2014-12-24 | 腾讯科技（深圳）有限公司 | Text message recommendation method, server, browser and system |
| CN107220386A (en) * | 2017-06-29 | 2017-09-29 | 北京百度网讯科技有限公司 | Information-pushing method and device |
| CN108228906A (en) * | 2018-02-08 | 2018-06-29 | 北京百度网讯科技有限公司 | For generating the method and apparatus of information |
-
2018
- 2018-07-23 CN CN201810810075.4A patent/CN110750707A/en active Pending
Patent Citations (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN104239298A (en) * | 2013-06-06 | 2014-12-24 | 腾讯科技（深圳）有限公司 | Text message recommendation method, server, browser and system |
| CN107220386A (en) * | 2017-06-29 | 2017-09-29 | 北京百度网讯科技有限公司 | Information-pushing method and device |
| CN108228906A (en) * | 2018-02-08 | 2018-06-29 | 北京百度网讯科技有限公司 | For generating the method and apparatus of information |
Non-Patent Citations (1)
| Title |
|---|
| 王兰成: "《网络舆情分析技术》", 31 October 2014, 国防工业出版社 * |
Cited By (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111797201A (en) * | 2020-06-23 | 2020-10-20 | 中民筑友建设科技集团有限公司 | BIM (building information modeling) model acquisition method, device, equipment and computer readable storage medium |
| CN112328805A (en) * | 2020-10-29 | 2021-02-05 | 北京华云安信息技术有限公司 | Entity mapping method of vulnerability description information and database table based on NLP |
| CN112487765A (en) * | 2020-11-23 | 2021-03-12 | 建信金融科技有限责任公司 | Method and device for generating notification text |
| CN112487765B (en) * | 2020-11-23 | 2022-10-04 | 中国建设银行股份有限公司 | Method and device for generating notification text |
| CN113409123A (en) * | 2021-07-01 | 2021-09-17 | 北京沃东天骏信息技术有限公司 | Information recommendation method, device, equipment and storage medium |
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