CN110377891B - Method, device and equipment for generating event analysis article and computer readable storage medium - Google Patents
Method, device and equipment for generating event analysis article and computer readable storage medium Download PDFInfo
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Abstract
The application provides a method, a device and equipment for generating an event analysis article and a computer-readable storage medium. According to the event analysis article of the event, the event knowledge graph can be effectively supplemented with more knowledge contents, the event can be reported, analyzed and predicted more comprehensively through the knowledge contents, the depth of the generated article can be effectively improved, the learning requirement of a user on the event can be met, the possibility of the article being adopted by the user is improved, and the reliability of the article generation is improved.
Description
[ technical field ] A method for producing a semiconductor device
The present application relates to an article generation technology, and in particular, to a method, an apparatus, a device, and a computer-readable storage medium for generating an event analysis article.
[ background of the invention ]
Today, with the rapid development of the internet, in the field of article generation, more and more articles are automatically generated by machines. The machine may automatically generate an event introduction article for the event based on the collected news about the event to simply introduce the event.
However, since the article of an event is generated completely according to the news related to the event, the content of the generated article may not meet the learning requirement of the user for the event, and the probability of being adopted by the user is not high, thereby reducing the reliability of the article generation.
[ summary of the invention ]
Aspects of the present application provide a method, an apparatus, a device, and a computer-readable storage medium for generating an event analysis article, so as to improve reliability of article generation.
One aspect of the present application provides a method for generating an event analysis article, including:
determining the associated information of an event by using an event knowledge graph, wherein the associated information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event;
acquiring the related content of the event by utilizing a participant knowledge graph and the event knowledge graph according to the related information of the event, wherein the related content of the event comprises introduction content of the event, field content of the event field and introduction content of the participant;
obtaining the influence content of the event by using a matter knowledge graph according to the association information of the event;
and organizing the associated content of the event and the influence content of the event to generate an event analysis article of the event.
Another aspect of the present application provides an event analysis article generation apparatus, including:
the event knowledge graph is used for determining the association information of the event, wherein the association information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event;
an obtaining unit, configured to obtain, according to the association information of the event, association content of the event by using a participant knowledge graph and the event knowledge graph, where the association content of the event includes introduction content of the event, domain content of the event domain, and introduction content of the participant;
the obtaining unit is further configured to obtain influence content of the event by using a case knowledge graph according to the associated information of the event;
and the generating unit is used for organizing and processing the related content of the event and the influence content of the event so as to generate an event analysis article of the event.
In another aspect of the present application, there is provided an apparatus, including:
one or more processors;
a storage device to store one or more programs,
when executed by the one or more processors, the one or more programs cause the one or more processors to implement a method of generating an event analysis article as provided in one aspect above.
In another aspect of the present application, a computer-readable storage medium is provided, on which a computer program is stored, and the program, when executed by a processor, implements the method for generating an event analysis article as provided in the above aspect.
According to the technical scheme, the method and the device for analyzing the event of the event comprise the steps of determining the relevant information of the event by using an event knowledge graph, wherein the relevant information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event, further obtaining the relevant content of the event by using the participant knowledge graph and the event knowledge graph according to the relevant information of the event, wherein the relevant content of the event comprises the introduction content of the event, the field content of the event field and the introduction content of the participant, and obtaining the influence content of the event by using a physics knowledge graph according to the relevant information of the event, so that the relevant content of the event and the influence content of the event can be organized and processed to generate the event analysis article of the event.
In addition, by adopting the technical scheme provided by the application, the event knowledge graph, the participant knowledge graph and the case knowledge graph are combined, so that the events can be effectively and comprehensively reported and analyzed, and possible influences can be further predicted.
In addition, by adopting the technical scheme provided by the application, the user experience can be effectively improved.
[ description of the drawings ]
In order to more clearly illustrate the technical solutions in the embodiments of the present application, the drawings needed to be used in the embodiments or the prior art descriptions will be briefly described below, and it is obvious that the drawings in the following description are some embodiments of the present application, and those skilled in the art can also obtain other drawings according to the drawings without inventive labor.
Fig. 1 is a schematic flowchart of a method for generating an event analysis article according to an embodiment of the present application;
fig. 2 is a schematic structural diagram of an apparatus for generating an event analysis article according to another embodiment of the present application;
FIG. 3 is a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present application.
[ detailed description ] A
In order to make the objects, technical solutions and advantages of the embodiments of the present application clearer, the technical solutions in the embodiments of the present application will be clearly and completely described below with reference to the drawings in the embodiments of the present application, and it is obvious that the described embodiments are some embodiments of the present application, but not all embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present application.
It should be noted that the terminal involved in the embodiments of the present application may include, but is not limited to, a mobile phone, a Personal Digital Assistant (PDA), a wireless handheld device, a Tablet Computer (Tablet Computer), a Personal Computer (PC), an MP3 player, an MP4 player, a wearable device (e.g., smart glasses, a smart watch, a smart bracelet, etc.), and the like.
In addition, the term "and/or" herein is only one kind of association relationship describing an associated object, and means that there may be three kinds of relationships, for example, a and/or B, which may mean: a exists alone, A and B exist simultaneously, and B exists alone. In addition, the character "/" herein generally indicates that the former and latter related objects are in an "or" relationship.
Fig. 1 is a schematic flow chart of a method for generating an event analysis article according to an embodiment of the present application, as shown in fig. 1.
101. Determining the associated information of the event by using an event knowledge graph, wherein the associated information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event.
102. And obtaining the associated content of the event by utilizing a participant knowledge graph and the event knowledge graph according to the associated information of the event, wherein the associated content of the event comprises introduction content of the event, field content of the event field and introduction content of the participant.
103. And obtaining the influence content of the event by utilizing a affair knowledge graph according to the associated information of the event.
104. And organizing the associated content of the event and the influence content of the event to generate an event analysis article of the event.
The events in the present application may be events occurring in various fields, for example, financial events occurring in financial fields, for example, investment financing events, and the like, and the present application is not particularly limited thereto.
Therefore, the automatic generation of the article of the event is realized, and the event can be reported, analyzed and predicted more comprehensively through the generated article.
It should be noted that part or all of the execution subjects of 101 to 104 may be an application located at the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) set in the application located at the local terminal, or may also be a processing engine located in a server on the network side, or may also be a distributed system located on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native app (native app) installed on the terminal, or may also be a web page program (webApp) of a browser on the terminal, and this embodiment is not particularly limited thereto.
In this way, the event knowledge graph is used to determine the associated information of the event, the associated information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event, and further, according to the associated information of the event, the participant knowledge graph and the event knowledge graph are used to obtain the associated content of the event, the associated content of the event comprises the introduction content of the event, the field content of the event field and the introduction content of the participant, and according to the associated information of the event, the event influence content is obtained by using the event knowledge graph, so that the associated content of the event and the influence content of the event can be organized and processed to generate the event analysis article of the event.
The so-called knowledge graph itself is a network knowledge base formed by linking entities with attributes through relations, and from the view point of the graph, the knowledge graph is essentially a concept network, wherein nodes represent entities (or concepts) in the physical world, and various semantic relations between the entities form edges in the network, and the edges are directional. Thus, a knowledge graph is a symbolic representation of the physical world.
The event knowledge graph, the participant knowledge graph and the matter knowledge graph are used for describing the knowledge graph of professional concepts in a specific direction.
The event knowledge graph may be used to represent content data for an event. The node data in the event knowledge graph may include, but is not limited to, the name of the event, the occurrence time of the event, the participant of the event, the field of the event to which the event belongs, and the event description, which is not particularly limited in this application.
For example, taking investment and purchase events as an example, the node data in the event knowledge graph adopted in the present application may be the name of the event, the occurrence time of the event, the investor, the invested party, the event field to which the event belongs, and the event introduction.
The participant knowledge graph may be used to represent content data of event participants. The node data in the participant knowledge graph may include, but is not limited to, the domain to which the participant belongs, event-related behavior of the participant, products and scope of services provided by the participant, management information of the participant, and upstream and downstream of an information chain in which the participant is located, which is not particularly limited in this application.
For example, taking an investment and purchase event as an example, the node data in the participant knowledge graph adopted in the present application may be the domain to which the enterprise belongs, the investment financing behavior of the enterprise, the service product and scope provided by the enterprise, the management information of the enterprise, and the upstream and downstream of the information chain in which the enterprise is located.
The event knowledge graph may be used to represent relationship data between participants of an event, where the relationship may include, but is not limited to, causal, sequential, and turning, and is not particularly limited in this application. The participant knowledge graph takes events as nodes and relations between the events as edges.
The application can be used for event inference through a case graph, for example: the influence, including positive influence and negative influence, generated after the event occurs is analyzed, and the possible influence is predicted.
Optionally, in a possible implementation manner of this embodiment, before 101, event corpus data may be further obtained according to an event that occurs in history and is the same as or similar to the name of the event, and further, the event knowledge graph, the participant knowledge graph, and the case knowledge graph may be constructed according to the event corpus data.
Specifically, the event knowledge graph, the participant knowledge graph, and the case knowledge graph may be constructed by using event corpus data using an existing knowledge graph construction method.
Optionally, in a possible implementation manner of this embodiment, in 104, the related content of the event and the influence content of the event may be specifically added to a preset article template, so as to generate an event analysis article of the event.
Specifically, the corresponding article template may be obtained according to the type of the event. The article template may be generated by using an existing template generation method, for example, machine learning, manual configuration, or the like.
Taking an investment financing event as an example, the article template corresponding to the type of the event may include, but is not limited to, at least one of the following content modules:
title and heading;
introduced by the investment enterprise;
the overall investment market in the investment domain;
correlated investment events within the investment domain;
investing in enterprises, competition and layout in the investment field.
Optionally, in a possible implementation manner of this embodiment, in 104, organization processing may be specifically performed on the associated content of the event and the influence content of the event according to a preset configuration file, so as to generate an event analysis article of the event.
Specifically, the corresponding configuration file may be obtained according to the type of the event. The configuration file may be generated by using an existing file generation method, for example, machine learning, manual configuration, or the like.
The technical solution provided by the present application will be described in detail below by taking the investment and purchase event "Baidu Tou Ma Car".
First, the event knowledgegraph can be used to determine the name of the event, "bout-wama car", the investment domain to which the event belongs as "driverless domain", the sponsor as "bout (lead casting"), and the sponsor as "wama car".
Then, according to the name of the event, namely ' Baidu-Tou-Ma-Do ' vehicle ', the introduction content data of the event, such as the occurrence time of the event, the investor, the invested party, the investment domain to which the event belongs, and the like, can be obtained by utilizing the event knowledge map.
Then, according to the fact that the invested party is a Wimama automobile, by means of the knowledge graph of the participating party, the field of the enterprise of the invested party, the service product and range provided by the enterprise, the management information of the enterprise, the upstream and downstream of the information chain where the enterprise is located and other enterprise basic situation introduction data can be obtained.
Further, event data of financing events of the invested party can be obtained by utilizing an event knowledge graph according to the invested party being a Wiuman automobile. Further, the event data may be further statistically processed to obtain statistical data, such as corporate shareholders, etc. In order to more clearly present the statistical data, the statistical data may be presented specifically by using a graph.
Then, event data of all investment financing events in the investment field can be obtained by utilizing the event knowledge graph according to the fact that the investment field to which the event belongs is the unmanned field. Furthermore, these event data may be further statistically processed to obtain statistical data, such as investment financing events and their investment financing amount. In order to more clearly present the statistical data, the statistical data may be presented specifically by using a graph.
Further, to make the statistics more meaningful, only the event data and statistics of the investment financing events within the most recent time horizon (e.g., the last 1 year) may be considered.
Further, enterprise financing data of all enterprises in the investment field, such as the number of financing rounds and the like, can be obtained by using the knowledge graph of the participants according to the fact that the investment field to which the event belongs is the 'unmanned field'. In order to more clearly present the obtained enterprise financing data, the enterprise financing data may specifically be presented using a chart.
Then, according to the fact that the investor is "hundred degree (receiving investment)", the knowledge graph of the participating party is utilized to obtain the business basic situation introduction data of the field to which the enterprise of the investor belongs, the service products and the range provided by the enterprise, the management information of the enterprise, the upstream and downstream of the information chain where the enterprise is located and the like.
Further, event data of all investment events in the last N (such as 1 year or 5 years) years of the investor can be obtained by using the event knowledge graph according to the fact that the investor is 'hundred-degree (leader investment'). Furthermore, the event data may be further statistically processed to obtain statistical data, such as the investment area, the amount of investment, and the like. In order to more clearly present the statistical data, the statistical data may be presented specifically by using a graph.
Further, to make the statistics more meaningful, only the event data and statistics of investment events within the most recent time frame (e.g., the last 1 year) may be considered.
Subsequently, the event knowledge graph can be utilized to determine that the competitive enterprise of the investor is "Tencent", and further, the event knowledge graph can be further utilized to obtain the event data of all investment events of the competitive enterprise in the last N (such as 1 year or 5 years) years. Furthermore, the event data may be further statistically processed to obtain statistical data, such as the investment field, the amount of investment, and the like. In order to show the statistical data more clearly, the statistical data can be shown by using a chart.
Further, event data of all investment events of each enterprise of the N enterprises with the largest investment quantity in the investment field can be obtained by using the event knowledge graph according to the fact that the investment field to which the event belongs is the 'unmanned field'. Further, the event data may be further statistically processed to obtain statistical data, such as the amount of investment, and the like. In order to show the statistical data more clearly, the statistical data can be shown by using a chart.
And finally, obtaining the relationship between the investor and the invested party by utilizing the knowledge map of the participating party according to the fact that the investor is hundredth (receiving investment) and the invested party is Wimama car.
Generally, a certain relationship often exists between the investor and the invested party, and the relationship can be specifically divided into three relationships, namely, a transverse investment relationship, a longitudinal investment relationship and a mixed investment relationship. The horizontal investment relation refers to that the fields of the investor and the invested party belong to similar industry fields, for example, the fields of the investor and the invested party belong to the retail industry field; the longitudinal investment relation means that the investor and the invested party have an upstream and downstream relation, for example, the investor belongs to the field of automobile industry, the invested party belongs to the field of battery industry, and then the investor and the invested party have an upstream and downstream relation; the mixed investment relation means that the fields of the investor and the invested party belong to different industrial fields, and a large enterprise is often used as the investor to invest a small enterprise.
After the relationship between the investor and the invested party is obtained, the event knowledge map can be further utilized to perform analysis processing so as to obtain the influence of the event, such as the influence of the event on the investor, the invested party and the investment field.
For the transverse investment relationship, the internal information of industries such as market share and the like of the investor and the invested party can be analyzed by utilizing a case-of-affair knowledge map, whether the internal information of industries such as the market share and the like is influenced after investment or not and whether the stock price of the investor and the invested party fluctuates or not can be judged; for the longitudinal investment relation, the supply relation of the investor and the invested party on the product can be analyzed by utilizing a matter knowledge map, whether the supply relation is influenced after investment or not and whether the stock price of the investor and the invested party fluctuates or not can be analyzed; for mixed investment relations, event impact of similar investment events of the investor can be analyzed by utilizing a matter knowledge graph.
After the above-mentioned associated content of the event and the influence content of the event are obtained, the associated content of the event and the influence content of the event may be added to a preset article template to generate an event analysis article of the event.
For example, the introduction content data of events such as the occurrence time of the event, the supplier, the investment domain to which the event belongs, and the like, can be added to the "title and the guidance" part in the article template, and some auxiliary vocabularies, such as a language sense vocabulary, a tone vocabulary, a grammar structure vocabulary, and the like, are adopted to be connected into paragraphs capable of expressing complete meanings;
or, for another example, the enterprise basic situation introduction data of the domain to which the invested party belongs, the service products and scope provided by the enterprise, the management information of the enterprise, the upstream and downstream of the information chain where the enterprise is located, and the event data and statistical data of all financing events of the invested party can be added to the "invested enterprise introduction" part in the article template, and auxiliary vocabularies, such as language vocabularies, tone vocabularies, grammatical structure vocabularies, and the like, and format symbols, such as form lines, chart lines, and the like, are adopted to connect the auxiliary vocabularies into paragraphs capable of expressing complete meanings;
or, for another example, the event data and statistical data of all investment financing events in the investment domain and the enterprise financing data of all enterprises in the investment domain may be added to the "overall investment market of the investment domain" part in the article template, and auxiliary vocabularies, such as language vocabularies, tone vocabularies, grammar structure vocabularies, and the like, and format symbols, such as table lines, chart lines, and the like, may be used to connect them into paragraphs capable of expressing complete meanings;
or, for another example, the event data and statistical data of the investment financing event in the recent time range (such as the recent 1 year) may be added to the "investment domain related investment event" part in the article template, and auxiliary words, such as words of language sense, words of tone, words of grammatical structure, etc., and format symbols, such as table lines, chart lines, etc., may be used to connect them into paragraphs capable of expressing complete meaning;
or, for another example, the introduction data of the enterprise basic situation such as the domain where the enterprise of the investor belongs, the service product and range provided by the enterprise, the management information of the enterprise, the upstream and downstream of the information chain where the enterprise is located, the event data and statistical data of all investment events in the last N years (such as 1 year or 5 years) of the investor, and the influence of the event can be added to the "investment enterprise, competition and layout in the investment domain" section of the article template, and the auxiliary words such as the language words, the tone words, the syntactic structure words, and the like, and the format symbols such as the table lines, the chart lines, and the like can be connected into the paragraphs capable of expressing the complete meaning.
Thus, the automatic generation of the event analysis article of the investment and purchase event 'Baidu Wai Ma automobile'. By combining the event knowledge map, the participant knowledge map and the affair knowledge map, more contents can be supplemented to the investment and purchase event 'Baidu TowerMa automobile', and the investment and purchase event 'Baidu TowerMa automobile' can be reported and analyzed more comprehensively through the supplemented contents.
In this embodiment, by using an event knowledge graph, determining associated information of an event, where the associated information of the event includes a name of the event, an event field to which the event belongs, and a participant of the event, and further, according to the associated information of the event, obtaining associated content of the event by using a participant knowledge graph and the event knowledge graph, where the associated content of the event includes introduction content of the event, field content of the event field, and introduction content of the participant, and obtaining influence content of the event by using a physics knowledge graph according to the associated information of the event, the associated content of the event and the influence content of the event can be organized and processed to generate an event analysis article of the event.
In addition, by adopting the technical scheme provided by the application and combining the event knowledge map, the participant knowledge map and the affair knowledge map, the events can be effectively reported and analyzed comprehensively, and possible influences can be further predicted.
In addition, by adopting the technical scheme provided by the application, the user experience can be effectively improved.
It should be noted that for simplicity of description, the above-mentioned embodiments of the method are described as a series of acts, but those skilled in the art should understand that the present application is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present application. Further, those skilled in the art will recognize that the embodiments described in this specification are preferred embodiments and that acts or modules referred to are not necessarily required for this application.
In the foregoing embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
Fig. 2 is a schematic structural diagram of an apparatus for generating an event analysis article according to another embodiment of the present application, as shown in fig. 2. The generation apparatus of the event analysis article of the present embodiment may include the determination unit 21, the obtaining unit 22, and the generation unit 23. The determining unit 21 is configured to determine, by using an event knowledge graph, associated information of an event, where the associated information of the event includes a name of the event, an event field to which the event belongs, and a participant of the event; an obtaining unit 22, configured to obtain, according to the association information of the event, associated content of the event by using a participant knowledge graph and the event knowledge graph, where the associated content of the event includes introduction content of the event, domain content of the event domain, and introduction content of the participant; the obtaining unit 22 is further configured to obtain, according to the associated information of the event, influence content of the event by using a case knowledge graph; the generating unit 23 is configured to perform organization processing on the associated content of the event and the influence content of the event to generate an event analysis article of the event.
The event in the present application may be an event occurring in each field, for example, a financial event occurring in a financial field, for example, an investment financing event, and the like, and the present application is not particularly limited thereto.
Therefore, the automatic generation of the article of the event is realized, and the event can be reported, analyzed and predicted more comprehensively through the generated article.
It should be noted that part or all of the apparatus for generating an event analysis article provided in this embodiment may be an application located in the local terminal, or may also be a functional unit such as a plug-in or Software Development Kit (SDK) that is set in the application located in the local terminal, or may also be a search engine that is located in a server on a network side, or may also be a distributed system that is located on the network side, which is not particularly limited in this embodiment.
It is to be understood that the application may be a native app (native app) installed on the terminal, or may also be a web page app (webApp) of a browser on the terminal, which is not particularly limited in this embodiment.
Optionally, in a possible implementation manner of this embodiment, the generating unit 23 may be specifically configured to add the content related to the event and the content affecting the event to a preset article template, and generate an event analysis article of the event.
Optionally, in a possible implementation manner of this embodiment, the generating unit 23 may be specifically configured to perform organization processing on the associated content of the event and the influence content of the event according to a preset configuration file, so as to generate an event analysis article of the event.
Optionally, in a possible implementation manner of this embodiment, the obtaining unit 22 may be further configured to obtain event corpus data according to an event that occurs in history and has the same or similar name as the event; and constructing the event knowledge graph, the participant knowledge graph and the affair knowledge graph according to the event corpus data.
It should be noted that the method in the embodiment corresponding to fig. 1 may be implemented by the apparatus for generating an event analysis article provided in this embodiment. For a detailed description, reference may be made to relevant contents in the embodiment corresponding to fig. 1, and details are not described here.
In this embodiment, the determining unit determines the associated information of the event by using an event knowledge graph, where the associated information of the event includes the name of the event, the event field to which the event belongs, and the participant of the event, and the obtaining unit obtains the associated content of the event by using the participant knowledge graph and the event knowledge graph according to the associated information of the event, where the associated content of the event includes the introduction content of the event, the field content of the event field, and the introduction content of the participant, and obtains the influence content of the event by using a physics knowledge graph according to the associated information of the event, so that the generating unit can organize and process the associated content of the event and the influence content of the event to generate an event analysis article of the event.
In addition, by adopting the technical scheme provided by the application, the event knowledge graph, the participant knowledge graph and the case knowledge graph are combined, so that the events can be effectively and comprehensively reported and analyzed, and possible influences can be further predicted.
In addition, by adopting the technical scheme provided by the application, the user experience can be effectively improved.
FIG. 3 illustrates a block diagram of an exemplary computer system/server 12 suitable for use in implementing embodiments of the present application. The computer system/server 12 shown in FIG. 3 is only an example and should not be taken to limit the scope of use or functionality of embodiments of the present application.
As shown in FIG. 3, computer system/server 12 is in the form of a general purpose computing device. The components of computer system/server 12 may include, but are not limited to: one or more processors or processing units 16, a storage device or system memory 28, and a bus 18 that couples various system components including the system memory 28 and the processing unit 16.
Computer system/server 12 typically includes a variety of computer system readable media. Such media may be any available media that is accessible by computer system/server 12 and includes both volatile and nonvolatile media, removable and non-removable media.
The system memory 28 may include computer system readable media in the form of volatile memory, such as Random Access Memory (RAM) 30 and/or cache memory 32. The computer system/server 12 may further include other removable/non-removable, volatile/nonvolatile computer system storage media. By way of example only, storage system 34 may be used to read from and write to non-removable, nonvolatile magnetic media (not shown in FIG. 3 and commonly referred to as a "hard drive"). Although not shown in FIG. 3, a magnetic disk drive for reading from and writing to a removable, nonvolatile magnetic disk (e.g., a "floppy disk") and an optical disk drive for reading from or writing to a removable, nonvolatile optical disk (e.g., a CD-ROM, DVD-ROM, or other optical media) may be provided. In these cases, each drive may be connected to bus 18 by one or more data media interfaces. System memory 28 may include at least one program product having a set (e.g., at least one) of program modules that are configured to carry out the functions of embodiments of the application.
A program/utility 40 having a set (at least one) of program modules 42 may be stored, for example, in system memory 28, such program modules 42 including, but not limited to, an operating system, one or more application programs, other program modules, and program data, each of which examples or some combination thereof may comprise an implementation of a network environment. Program modules 42 generally perform the functions and/or methodologies of the embodiments described herein.
The computer system/server 12 may also communicate with one or more external devices 14 (e.g., keyboard, pointing device, display 25, etc.), with one or more devices that enable a user to interact with the computer system/server 12, and/or with any devices (e.g., network card, modem, etc.) that enable the computer system/server 12 to communicate with one or more other computing devices. Such communication may be through an input/output (I/O) interface 44. Also, the computer system/server 12 may communicate with one or more networks (e.g., a Local Area Network (LAN), a Wide Area Network (WAN) and/or a public network, such as the Internet) via the network adapter 20. As shown, network adapter 20 communicates with the other modules of computer system/server 12 via bus 18. It should be understood that although not shown in the figures, other hardware and/or software modules may be used in conjunction with computer system/server 12, including but not limited to: microcode, device drivers, redundant processing units, external disk drive arrays, RAID systems, tape drives, and data backup storage systems, among others.
The processing unit 16 executes various functional applications and data processing by executing programs stored in the system memory 28, for example, implementing the method for generating the event analysis article provided in the embodiment corresponding to fig. 1.
Another embodiment of the present application further provides a computer-readable storage medium, on which a computer program is stored, where the computer program, when executed by a processor, implements the method for generating an event analysis article provided in the embodiment corresponding to fig. 1.
In particular, any combination of one or more computer-readable media may be employed. The computer readable medium may be a computer readable signal medium or a computer readable storage medium. 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 (a non-exhaustive list) of the computer readable storage medium would include the following: 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. In the context of this document, a computer readable storage medium may be any tangible medium that can contain, or store a program for use by or in connection with an instruction execution system, apparatus, or device.
A computer readable signal medium may include a propagated data signal with computer readable program code embodied therein, for example, in baseband or as part of a carrier wave. Such a propagated data signal may take any of a variety of forms, including, but not limited to, electro-magnetic, optical, or any suitable combination thereof. A computer readable signal medium may also be any computer readable medium that is not a computer readable storage medium and that can communicate, propagate, or transport a program for use by or in connection with an instruction execution system, apparatus, or device.
Program code embodied on a computer readable medium may be transmitted using any appropriate medium, including but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.
Computer program code for carrying out operations for aspects of the present application may be written in any combination of one or more programming languages, including an object oriented programming language such as Java, smalltalk, C + +, and conventional procedural programming languages, such as the "C" programming language or similar programming languages. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer or entirely on the remote computer or server. In the case of a remote computer, the remote computer may be connected to the user's computer through any type of network, including a Local Area Network (LAN) or a Wide Area Network (WAN), or the connection may be made to an external computer (for example, through the Internet using an Internet service provider).
It is clear to those skilled in the art that, for convenience and brevity of description, the specific working processes of the above-described systems, apparatuses and units may refer to the corresponding processes in the foregoing method embodiments, and are not described herein again.
In the several embodiments provided in the present application, it should be understood that the disclosed system, apparatus and method may be implemented in other manners. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one type of logical functional division, and other divisions may be realized in practice, for example, multiple units or page components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one position, or may be distributed on multiple network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present application may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit may be implemented in the form of hardware, or in the form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present application. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, an optical disk, or other various media capable of storing program codes.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solutions of the present application, and not to limit the same; although the present application has been described in detail with reference to the foregoing embodiments, it should be understood by those of ordinary skill in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some technical features may be equivalently replaced; and such modifications or substitutions do not depart from the spirit and scope of the corresponding technical solutions of the embodiments of the present application.
Claims (10)
1. A method for generating an event analysis article is characterized by comprising the following steps:
determining the associated information of an event by using an event knowledge graph, wherein the associated information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event;
acquiring the related content of the event by utilizing a participant knowledge graph and the event knowledge graph according to the related information of the event, wherein the related content of the event comprises introduction content of the event, field content of the event field and introduction content of the participant;
obtaining the influence content of the event by using a matter knowledge graph according to the association information of the event;
and organizing the associated content of the event and the influence content of the event to generate an event analysis article of the event.
2. The method of claim 1, wherein the organizing the associated content of the event and the influence content of the event to generate an event analysis article of the event comprises:
adding the related content of the event and the influence content of the event into a preset article template to generate an event analysis article of the event; or alternatively
And organizing the related content of the event and the influence content of the event according to a preset configuration file to generate an event analysis article of the event.
3. The method of claim 1, further comprising:
obtaining event corpus data according to events which occur in history and have the same or similar names with the events;
and constructing the event knowledge graph, the participant knowledge graph and the affair knowledge graph according to the event corpus data.
4. A method according to any one of claims 1 to 3, wherein the event comprises a financial event.
5. An apparatus for generating an event analysis article, comprising:
the event knowledge graph is used for determining the association information of the event, wherein the association information of the event comprises the name of the event, the event field to which the event belongs and the participant of the event;
an obtaining unit, configured to obtain, according to the association information of the event, association content of the event by using a participant knowledge graph and the event knowledge graph, where the association content of the event includes introduction content of the event, domain content of the event domain, and introduction content of the participant;
the obtaining unit is further configured to obtain the influence content of the event by using a case knowledge graph according to the association information of the event;
and the generating unit is used for organizing and processing the related content of the event and the influence content of the event so as to generate an event analysis article of the event.
6. Device according to claim 5, characterized in that the generating unit is specifically configured to
Adding the related content of the event and the influence content of the event into a preset article template to generate an event analysis article of the event; or
And organizing the associated content of the event and the influence content of the event according to a preset configuration file to generate an event analysis article of the event.
7. The apparatus of claim 5, wherein the obtaining unit is further configured to obtain the second data
Obtaining event corpus data according to events which are historically generated and have the same or similar names with the events; and
and constructing the event knowledge graph, the participant knowledge graph and the affair knowledge graph according to the event corpus data.
8. An apparatus as claimed in any one of claims 5 to 7, wherein the event comprises a financial event.
9. An electronic device, characterized in that the electronic device comprises:
one or more processors;
a storage device to store 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 1-4.
10. A computer-readable storage 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 to 4.
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| US9619450B2 (en) * | 2013-06-27 | 2017-04-11 | Google Inc. | Automatic generation of headlines |
| CN106844322A (en) * | 2017-01-22 | 2017-06-13 | 百度在线网络技术（北京）有限公司 | Intelligent article generation method and device |
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| CN109902302B (en) * | 2019-03-01 | 2020-03-24 | 郑敏杰 | Topic map generation method, device and equipment suitable for text analysis or data mining and computer storage medium |
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