CN111221978A - Method and device for constructing knowledge graph, computer storage medium and terminal - Google Patents
Method and device for constructing knowledge graph, computer storage medium and terminal Download PDFInfo
- Publication number
- CN111221978A CN111221978A CN201911417223.7A CN201911417223A CN111221978A CN 111221978 A CN111221978 A CN 111221978A CN 201911417223 A CN201911417223 A CN 201911417223A CN 111221978 A CN111221978 A CN 111221978A
- Authority
- CN
- China
- Prior art keywords
- data
- event
- decision
- enterprise
- information
- 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
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/30—Information retrieval; Database structures therefor; File system structures therefor of unstructured textual data
- G06F16/36—Creation of semantic tools, e.g. ontology or thesauri
- G06F16/367—Ontology
Abstract
A method, a device, a computer storage medium and a terminal for constructing a knowledge graph comprise the following steps: acquiring event related data; analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event; constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event; wherein the event related data comprises one or any combination of the following items: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data. According to the embodiment of the invention, the knowledge graph is constructed based on the decision behavior information and the decision influence information of the event, so that the application efficiency of the internal data of the enterprise is improved, and information support is provided for improving the decision quality of the enterprise.
Description
Technical Field
The present disclosure relates to, but not limited to, information analysis technologies, and more particularly, to a method, an apparatus, a computer storage medium, and a terminal for constructing a knowledge graph.
Background
Currently, decisions in enterprises mostly depend on data of business processing, and the processing speed and efficiency of the enterprise business can be effectively improved through the decisions obtained by the data; however, most of the data in the enterprise is scattered at present, and data support cannot be provided for enterprise decision making. Fig. 1 is a schematic diagram of an internal component structure of an enterprise, as shown in fig. 1, the enterprise includes a plurality of component departments, different component departments use different systems, events (call back failure, honor reward, employee violation, etc.) occurred in different departments usually generate different decisions, and the decision content is usually stored in different systems in the manners of meeting summary and document record; because the events and the decision information are stored dispersedly, enterprise personnel cannot refer to the existing data of all aspects to make enterprise decisions for influencing different decisions, and therefore the enterprise decisions are made possibly to fail to obtain expected effects; in addition, there are a number of processes within an enterprise that can help enterprise personnel determine enterprise decisions: institutional documents, organizational documents, incident summary documents, meeting documents, etc., but reviewing these documents requires a significant amount of time and effort, making such data inefficiently utilized.
In summary, data that can be used for assisting enterprise decision making is generally dispersed in systems of different departments, and enterprise personnel cannot make enterprise decision effectively, so that how to improve the application efficiency of internal data of an enterprise and the quality of enterprise decision making becomes a problem to be solved.
Disclosure of Invention
The following is a summary of the subject matter described in detail herein. This summary is not intended to limit the scope of the claims.
The embodiment of the invention provides a method and a device for constructing a knowledge graph, a computer storage medium and a terminal, which can improve the application efficiency of internal data of an enterprise and improve the decision quality of the enterprise.
The embodiment of the invention provides a method for constructing a knowledge graph, which comprises the following steps:
acquiring event related data;
analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event;
constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event;
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
In one exemplary embodiment:
when the event related data includes the event processing data, the event processing data includes: recording file data of the event and/or processing result data of the event;
when the event related data includes the enterprise internal flow data, the enterprise internal flow data includes: processing flow documents aiming at various events, which are stored by enterprises;
when the event-related data includes the sales analysis data, the sales analysis data includes: data on sales and/or revenue;
when the event related data comprises the public opinion analysis data, the public opinion analysis data comprises network data of one or any combination of the following items: enterprise-related comments, enterprise-related complaints, enterprise-related news, enterprise-related public relationship PR texts, enterprise product-related comments, enterprise product-related complaints, enterprise product-related news, enterprise product-related PR texts;
when the event related data comprises the other unclassified associated data, the other unclassified associated data comprises one or more of the following unclassified data: document data, picture data, compressed data, mail data, video data.
In an exemplary embodiment, the event related data includes: the event processing data, the enterprise internal flow data and the other unclassified associated data, and the analyzing the obtained event related data include:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and the decision behavior information corresponding to the event; and/or the presence of a gas in the gas,
determining events and the decision-making behavior information corresponding to the events according to event-related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keyword, time and place.
In an exemplary embodiment, after obtaining the decision behavior information of each event, the method further includes:
carrying out similarity judgment on the decision-making behavior information, and combining the decision-making behavior information judged to be similar into decision-making behavior information; and/or the presence of a gas in the gas,
determining the decision type of each decision behavior information according to a preset classification strategy; and according to the determined decision category, classifying and storing the decision behavior information.
In an exemplary embodiment, the event related data includes: the event processing data, the sales analysis data and the public opinion analysis data, the event related data obtained by analysis includes the decision impact information obtained by one or any combination of the following processes:
analyzing the public opinion analysis data to determine public opinion influence information corresponding to each event;
analyzing the sales analysis data to obtain financial impact information corresponding to each event;
and analyzing the event processing data to obtain user influence information corresponding to each event.
In an exemplary embodiment, after the constructing the knowledge-graph, the method further comprises:
and respectively setting access authority for accessing the generated knowledge graph for each user.
On the other hand, the embodiment of the invention also provides a device for constructing the knowledge graph, which comprises the following steps: the device comprises an acquisition unit, an analysis unit and a construction unit; wherein the content of the first and second substances,
the acquisition unit is used for: acquiring event related data;
the analysis unit is used for: analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event;
the building unit is used for: constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event;
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
In an exemplary embodiment, the event related data includes: the event processing data, the sales analysis data, the public opinion analysis data, the enterprise internal flow data and the other unclassified associated data; the analysis unit comprises a first analysis module and a second analysis module; wherein the first parsing module is configured to:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and the decision behavior information corresponding to the event; and/or the presence of a gas in the gas,
determining events and the decision-making behavior information corresponding to the events according to event-related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keywords, time and place;
the second parsing module is configured to obtain the decision impact information through one or any combination of the following processes:
analyzing the public opinion analysis data to determine public opinion influence information corresponding to each event;
analyzing the sales analysis data to obtain financial impact information corresponding to each event;
and analyzing the event processing data to obtain user influence information corresponding to each event.
In still another aspect, an embodiment of the present invention further provides a computer storage medium, where a computer program is stored, and when the computer program is executed by a processor, the method for constructing a knowledge graph is implemented.
In another aspect, an embodiment of the present invention further provides a terminal, including: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of constructing a knowledge-graph as described above.
Compared with the related art, the technical scheme of the application comprises the following steps: acquiring event related data; analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event; constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event; wherein the event related data comprises one or any combination of the following items: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data. According to the embodiment of the invention, the knowledge graph is constructed based on the decision behavior information and the decision influence information of the event, so that the application efficiency of the internal data of the enterprise is improved, and information support is provided for improving the decision quality of the enterprise.
Additional features and advantages of the invention will be set forth in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. The objectives and other advantages of the invention will be realized and attained by the structure particularly pointed out in the written description and claims hereof as well as the appended drawings.
Drawings
The accompanying drawings are included to provide a further understanding of the invention and are incorporated in and constitute a part of this specification, illustrate embodiments of the invention and together with the example serve to explain the principles of the invention and not to limit the invention.
FIG. 1 is a schematic diagram of an internal component structure of an enterprise;
FIG. 2 is a flow diagram of a method of constructing a knowledge-graph according to an embodiment of the present invention;
FIG. 3 is a diagram illustrating event review by a constructed knowledge graph according to an embodiment of the present invention;
FIG. 4 is a block diagram of an apparatus for constructing a knowledge graph according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the present invention more apparent, embodiments of the present invention will be described in detail below with reference to the accompanying drawings. It should be noted that the embodiments and features of the embodiments in the present application may be arbitrarily combined with each other without conflict.
The steps illustrated in the flow charts of the figures may be performed in a computer system such as a set of computer-executable instructions. Also, while a logical order is shown in the flow diagrams, in some cases, the steps shown or described may be performed in an order different than here.
FIG. 2 is a flowchart of a method for constructing a knowledge graph according to an embodiment of the present invention, as shown in FIG. 2, including:
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
In one exemplary embodiment, when the event related data includes event processing data, the event processing data includes: recording file data of the event and/or processing result data of the event; taking the maintenance product as an example, the method can comprise the following steps: maintenance documents, complaint information, review information, Public Relations (PR) documents, and the like;
in one exemplary embodiment, when the event-related data includes enterprise internal flow data, the enterprise internal flow data includes: processing flow documents aiming at various events, which are stored by enterprises; such as complaint handling process flow documents.
In one exemplary embodiment, when the event-related data includes sales analysis data, the sales analysis data includes: data on sales and/or revenue; it should be noted that sales analysis data is typically organized based on time and/or region.
In an exemplary embodiment, when the event related data includes public opinion analysis data, the public opinion analysis data includes network data of one or any combination of the following items: enterprise-related comments, enterprise-related complaints, enterprise-related news, enterprise-related PR text, enterprise product-related comments, enterprise product-related complaints, enterprise product-related news, and enterprise product-related PR text.
It should be noted that the public opinion analysis data can be captured and stored by the public opinion analysis system.
In an exemplary embodiment, when the event related data includes other unclassified associated data, the other unclassified associated data includes one or more of the following unclassified data: document data, picture data, compressed data, mail data, video data, and the like.
It should be noted that the event-related data may be a file exported by an internal system of the enterprise or data exported using an application-level Application Program Interface (API); the event related data may include data distributed across a plurality of distributed systems.
in an exemplary embodiment, the event related data includes: the event processing data, the enterprise internal flow data and the other unclassified associated data, and the analyzing the obtained event related data include:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and decision behavior information corresponding to the event; here, analyzing the event processing data and/or the other unclassified associated data through a decision flow template includes: and analyzing the event processing data and/or the other unclassified associated data through a decision flow template to perform text analysis.
Determining events and decision behavior information corresponding to the events according to event related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keyword, time and place.
In an exemplary embodiment, the embodiment of the present invention may obtain decision behavior information of an event according to a keyword of the event; in the embodiment of the present invention, the decision behavior information is generally information for processing an event within a certain time interval of the event occurrence. Different enterprises have different types of events, the keywords for acquiring the decision behavior information are different, and technicians in the field can store the keywords of various types of events according to event classification so as to conveniently acquire the decision information; different departments of an enterprise may have different decision-making behavior information aiming at the same event, and the decision-making behavior information of a plurality of departments can be obtained by acquiring the decision-making behavior information in the event time interval according to the keywords of the event.
In an exemplary embodiment, the method of an embodiment of the present invention further includes: judging the similarity of the decision-making behavior information corresponding to the events, and merging the decision-making behavior information judged to be similar; the method for judging the similarity includes an analysis method existing in the related art, for example, a text analysis method.
In an exemplary embodiment, the method of an embodiment of the present invention further includes:
determining the decision type of each decision behavior information according to a preset classification strategy;
classifying and storing the decision behavior information according to the determined decision category;
in an exemplary embodiment, determining a decision category of each of the decision behavior information according to a preset classification policy includes: performing part-of-speech analysis on the keywords of the decision-making behavior information to determine whether the keywords are synonyms or not; defining the keywords with lower word frequency in the synonyms as the keywords with higher word frequency, and then carrying out word frequency statistics; determining the classification of the decision behavior information according to one or more keywords with the highest word frequency; for example, decision behavior information for negotiating with a customer's telephone, negotiating with a customer's mail, and negotiating with a customer's meeting is categorized into a category of negotiation with a customer.
It should be noted that, after determining the classification of the decision behavior information, the embodiment of the present invention may adjust the classification information by a person skilled in the art. After classification is completed, the decision behavior information can be classified and displayed in the knowledge graph.
In an exemplary embodiment, the decision impact information includes one or any combination of the following:
public opinion influence information, financial influence information, user influence information.
In the embodiment of the present invention, the public opinion influence information includes but is not limited to: the impact of events on public praise, brands, etc. of an enterprise or its products; the public opinion influence information can be obtained by crawling the network data aiming at the event in the event occurrence time period through the existing public opinion analysis system in the related technology, and analyzing the crawled network data to determine the emotion score and the event popularity. For example, in a product maintenance event, a public opinion analysis system captures comments related to the event on a network to obtain the number of positive comments and negative comments, so as to calculate an emotion score; and analyzing the number change trend of the comments and the related articles of the event to determine the event popularity.
Financial impact information includes, but is not limited to: impact on product sales, pricing, profits, enterprise funds, etc.; the financial impact information may include: obtained from sales analysis data: sales and revenue data corresponding to the time and area of occurrence of the event.
User impact information includes, but is not limited to: complaints, comments, etc. The method can comprise the following steps: analyzing the event processing data to obtain user influence information corresponding to each event; specifically, the method may include: obtaining and counting feedback contents such as user complaints and comments received by after-sales departments within the time range of event generation; and extracting keywords and/or key phrases from the feedback content, and using the extracted keywords and/or key phrases as user influence information.
In an exemplary embodiment, embodiments of the present invention perform other impact analyses based on industry data sources and evaluation criteria.
The decision-making behavior information and the influence result information are not in time precedence relationship, and the decision-making behavior information and the influence result information can establish an incidence relationship based on events.
In an exemplary embodiment, when information of one or more events recorded in the same document is extracted based on decision behavior information and influence result information, an association relationship between the decision behavior information and the influence result information may be established based on a timeline.
In an exemplary embodiment, one decision behavior information may be associated with one or more items of influence result information; each impact result information may also result from one or more decision behavior information. In the knowledge graph, the causal relationship is extracted based on a time axis, the decision behavior information is used as the content of the decision node, the influence result information is used as the content of the influence node, the association relationship between the decision behavior information and the influence result information is established, the decision node and the influence node are connected, and the construction of the knowledge graph is completed after the decision node and the influence node are associated with corresponding data files.
And step 203, constructing a knowledge graph according to the decision behavior information and the decision influence information of each event obtained by analysis.
It should be noted that, after determining an event, and decision behavior information and decision influence information corresponding to the event, the embodiment of the present invention may construct and generate a knowledge graph according to the correlation principle. In addition, the embodiment of the invention can set decision nodes and influence nodes in the constructed knowledge graph to be used for loading and displaying decision behavior information and decision influence information respectively.
In an exemplary embodiment, the method of an embodiment of the present invention further includes: and respectively setting access authority for accessing the generated knowledge graph for each user.
After the knowledge graph is generated, the knowledge graph can be searched and used according to a relevant principle; for example, related events are queried by event name. FIG. 3 is a schematic diagram of event review by the constructed knowledge-graph according to the embodiment of the present invention, as shown in FIG. 3, including: when the quality of the product is in question, the after-sale department, the official department and the financial part all participate in the decision-making behavior of the product after sale. And corresponding treatment is carried out on different departments according to different conditions.
Compared with the related art, the technical scheme of the application comprises the following steps: acquiring event related data; analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event; constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event; wherein the event related data comprises one or any combination of the following items: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data. According to the embodiment of the invention, the knowledge graph is constructed based on the decision behavior information and the decision influence information of the event, so that the application efficiency of the internal data of the enterprise is improved, and information support is provided for improving the decision quality of the enterprise.
Fig. 4 is a block diagram of an apparatus for constructing a knowledge graph according to an embodiment of the present invention, as shown in fig. 4, including: the device comprises an acquisition unit, an analysis unit and a construction unit; wherein the content of the first and second substances,
the acquisition unit is used for: acquiring event related data;
the analysis unit is used for: analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event;
the building unit is used for: constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event;
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
In one exemplary embodiment:
when the event related data includes the event processing data, the event processing data includes: recording file data of the event and/or processing result data of the event;
when the event related data includes the enterprise internal flow data, the enterprise internal flow data includes: processing flow documents aiming at various events, which are stored by enterprises;
when the event-related data includes the sales analysis data, the sales analysis data includes: data on sales and/or revenue;
when the event related data comprises the public opinion analysis data, the public opinion analysis data comprises network data of one or any combination of the following items: enterprise-related comments, enterprise-related complaints, enterprise-related news, enterprise-related public relationship PR texts, enterprise product-related comments, enterprise product-related complaints, enterprise product-related news, enterprise product-related PR texts;
when the event related data comprises the other unclassified associated data, the other unclassified associated data comprises one or more of the following unclassified data: document data, picture data, compressed data, mail data, video data.
In an exemplary embodiment, the event related data includes: the event processing data, the sales analysis data, the public opinion analysis data, the enterprise internal flow data and the other unclassified associated data; the analysis unit comprises a first analysis module and a second analysis module; wherein the first parsing module is configured to:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and the decision behavior information corresponding to the event; and/or the presence of a gas in the gas,
determining events and the decision-making behavior information corresponding to the events according to event-related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keywords, time and place;
the second parsing module is configured to obtain the decision impact information through one or any combination of the following processes:
analyzing the public opinion analysis data to determine public opinion influence information corresponding to each event;
analyzing the sales analysis data to obtain financial impact information corresponding to each event;
and analyzing the event processing data to obtain user influence information corresponding to each event.
In an exemplary embodiment, the apparatus further comprises a decision processing unit configured to:
carrying out similarity judgment on the decision-making behavior information, and combining the decision-making behavior information judged to be similar into decision-making behavior information; and/or the presence of a gas in the gas,
determining the decision type of each decision behavior information according to a preset classification strategy; and according to the determined decision category, classifying and storing the decision behavior information.
In an exemplary embodiment, the apparatus further includes a permission setting unit to:
and respectively setting access authority for accessing the generated knowledge graph for each user.
Compared with the related art, the technical scheme of the application comprises the following steps: acquiring event related data; analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event; constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event; wherein the event related data comprises one or any combination of the following items: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data. According to the embodiment of the invention, the knowledge graph is constructed based on the decision behavior information and the decision influence information of the event, so that the application efficiency of the internal data of the enterprise is improved, and information support is provided for improving the decision quality of the enterprise.
The embodiment of the invention also provides a computer storage medium, wherein a computer program is stored in the computer storage medium, and when being executed by a processor, the computer program realizes the method for constructing the knowledge graph.
An embodiment of the present invention further provides a terminal, including: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program, when executed by the processor, implements a method of constructing a knowledge-graph as described above.
"one of ordinary skill in the art will appreciate that all or some of the steps of the methods, systems, functional modules/units in the devices disclosed above may be implemented as software, firmware, hardware, and suitable combinations thereof. In a hardware implementation, the division between functional modules/units mentioned in the above description does not necessarily correspond to the division of physical components; for example, one physical component may have multiple functions, or one function or step may be performed by several physical components in cooperation. Some or all of the components may be implemented as software executed by a processor, such as a digital signal processor or microprocessor, or as hardware, or as an integrated circuit, such as an application specific integrated circuit. Such software may be distributed on computer readable media, which may include computer storage media (or non-transitory media) and communication media (or transitory media). The term computer storage media includes volatile and nonvolatile, removable and non-removable media implemented in any method or technology for storage of information such as computer readable instructions, data structures, program modules or other data, as is well known to those of ordinary skill in the art. Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technology, CD-ROM, Digital Versatile Disks (DVD) or other optical disk storage, magnetic cassettes, magnetic tape, magnetic disk storage or other magnetic storage devices, or any other medium which can be used to store the desired information and which can accessed by a computer. In addition, communication media typically embodies computer readable instructions, data structures, program modules or other data in a modulated data signal such as a carrier wave or other transport mechanism and includes any information delivery media as known to those skilled in the art. "
Claims (10)
1. A method of constructing a knowledge graph, comprising:
acquiring event related data;
analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event;
constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event;
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
2. The method of claim 1,
when the event related data includes the event processing data, the event processing data includes: recording file data of the event and/or processing result data of the event;
when the event related data includes the enterprise internal flow data, the enterprise internal flow data includes: processing flow documents aiming at various events, which are stored by enterprises;
when the event-related data includes the sales analysis data, the sales analysis data includes: data on sales and/or revenue;
when the event related data comprises the public opinion analysis data, the public opinion analysis data comprises network data of one or any combination of the following items: enterprise-related comments, enterprise-related complaints, enterprise-related news, enterprise-related public relationship PR texts, enterprise product-related comments, enterprise product-related complaints, enterprise product-related news, enterprise product-related PR texts;
when the event related data comprises the other unclassified associated data, the other unclassified associated data comprises one or more of the following unclassified data: document data, picture data, compressed data, mail data, and video data.
3. The method according to claim 1 or 2, wherein the event related data comprises: the event processing data, the enterprise internal flow data and the other unclassified associated data, and the analyzing the obtained event related data include:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and the decision behavior information corresponding to the event; and/or the presence of a gas in the gas,
determining events and the decision-making behavior information corresponding to the events according to event-related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keyword, time and place.
4. The method according to claim 1 or 2, wherein after obtaining the decision behavior information of each event, the method further comprises:
carrying out similarity judgment on the decision-making behavior information, and combining the decision-making behavior information judged to be similar into decision-making behavior information; and/or the presence of a gas in the gas,
determining the decision type of each decision behavior information according to a preset classification strategy; and according to the determined decision category, classifying and storing the decision behavior information.
5. The method according to claim 1 or 2, wherein the event related data comprises: the event processing data, the sales analysis data and the public opinion analysis data, the event related data obtained by analysis includes the decision impact information obtained by one or any combination of the following processes:
analyzing the public opinion analysis data to determine public opinion influence information corresponding to each event;
analyzing the sales analysis data to obtain financial impact information corresponding to each event;
and analyzing the event processing data to obtain user influence information corresponding to each event.
6. The method of claim 1 or 2, wherein after the construction of the knowledge-graph, the method further comprises:
and respectively setting access authority for accessing the generated knowledge graph for each user.
7. An apparatus for constructing a knowledge graph, comprising: the device comprises an acquisition unit, an analysis unit and a construction unit; wherein the content of the first and second substances,
the acquisition unit is used for: acquiring event related data;
the analysis unit is used for: analyzing the acquired event related data to acquire decision behavior information and decision influence information of each event;
the building unit is used for: constructing a knowledge graph according to the obtained decision behavior information and decision influence information of each event;
wherein the event related data comprises one or any combination of the following: event processing data, enterprise internal flow data, sales analysis data, public opinion analysis data and other unclassified associated data.
8. The apparatus of claim 7, wherein the event related data comprises: the event processing data, the sales analysis data, the public opinion analysis data, the enterprise internal flow data and the other unclassified associated data; the analysis unit comprises a first analysis module and a second analysis module; wherein the content of the first and second substances,
the first parsing module is configured to:
analyzing the internal process data of the enterprise to obtain a decision process template for event processing; analyzing the event processing data and/or the other unclassified associated data according to the obtained decision flow template, and determining an event and the decision behavior information corresponding to the event; and/or the presence of a gas in the gas,
determining events and the decision-making behavior information corresponding to the events according to event-related information from the event processing data and/or the other unclassified associated data;
wherein the event related information comprises one or more of the following event information: keywords, time and place;
the second parsing module is configured to obtain the decision impact information through one or any combination of the following processes:
analyzing the public opinion analysis data to determine public opinion influence information corresponding to each event;
analyzing the sales analysis data to obtain financial impact information corresponding to each event;
and analyzing the event processing data to obtain user influence information corresponding to each event.
9. A computer storage medium having stored thereon a computer program which, when executed by a processor, implements a method of constructing a knowledge-graph as claimed in any one of claims 1 to 6.
10. A terminal, comprising: a memory and a processor, the memory having a computer program stored therein; wherein the content of the first and second substances,
the processor is configured to execute the computer program in the memory;
the computer program when executed by the processor implements a method of constructing a knowledge graph as claimed in any one of claims 1 to 6.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911417223.7A CN111221978A (en) | 2019-12-31 | 2019-12-31 | Method and device for constructing knowledge graph, computer storage medium and terminal |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201911417223.7A CN111221978A (en) | 2019-12-31 | 2019-12-31 | Method and device for constructing knowledge graph, computer storage medium and terminal |
Publications (1)
| Publication Number | Publication Date |
|---|---|
| CN111221978A true CN111221978A (en) | 2020-06-02 |
Family
ID=70832768
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201911417223.7A Pending CN111221978A (en) | 2019-12-31 | 2019-12-31 | Method and device for constructing knowledge graph, computer storage medium and terminal |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN111221978A (en) |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111859969A (en) * | 2020-07-20 | 2020-10-30 | 航天科工智慧产业发展有限公司 | Data analysis method and device, electronic equipment and storage medium |
| CN111859969B (en) * | 2020-07-20 | 2024-05-03 | 航天科工智慧产业发展有限公司 | Data analysis method and device, electronic equipment and storage medium |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8019638B1 (en) * | 2002-08-21 | 2011-09-13 | DecisionStreet, Inc. | Dynamic construction of business analytics |
| CN107783973A (en) * | 2016-08-24 | 2018-03-09 | 慧科讯业有限公司 | The methods, devices and systems being monitored based on domain knowledge spectrum data storehouse to the Internet media event |
| CN107945024A (en) * | 2017-12-12 | 2018-04-20 | 厦门市美亚柏科信息股份有限公司 | Identify that internet finance borrowing enterprise manages abnormal method, terminal device and storage medium |
| CN109840268A (en) * | 2018-12-23 | 2019-06-04 | 国网浙江省电力有限公司 | A kind of universe data map construction method based on enterprise information model |
| CN110472884A (en) * | 2019-08-20 | 2019-11-19 | 深圳前海微众银行股份有限公司 | ESG index monitoring method, device, terminal device and storage medium |
-
2019
- 2019-12-31 CN CN201911417223.7A patent/CN111221978A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| US8019638B1 (en) * | 2002-08-21 | 2011-09-13 | DecisionStreet, Inc. | Dynamic construction of business analytics |
| CN107783973A (en) * | 2016-08-24 | 2018-03-09 | 慧科讯业有限公司 | The methods, devices and systems being monitored based on domain knowledge spectrum data storehouse to the Internet media event |
| CN107945024A (en) * | 2017-12-12 | 2018-04-20 | 厦门市美亚柏科信息股份有限公司 | Identify that internet finance borrowing enterprise manages abnormal method, terminal device and storage medium |
| CN109840268A (en) * | 2018-12-23 | 2019-06-04 | 国网浙江省电力有限公司 | A kind of universe data map construction method based on enterprise information model |
| CN110472884A (en) * | 2019-08-20 | 2019-11-19 | 深圳前海微众银行股份有限公司 | ESG index monitoring method, device, terminal device and storage medium |
Non-Patent Citations (1)
| Title |
|---|
| 高靖宇: ""基于知识图谱实现企业文档知识化管理研究"", 《中国科技纵横》 * |
Cited By (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN111859969A (en) * | 2020-07-20 | 2020-10-30 | 航天科工智慧产业发展有限公司 | Data analysis method and device, electronic equipment and storage medium |
| CN111859969B (en) * | 2020-07-20 | 2024-05-03 | 航天科工智慧产业发展有限公司 | Data analysis method and device, electronic equipment and storage medium |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| Japec et al. | Big data in survey research: AAPOR task force report | |
| US10496815B1 (en) | System, method, and computer program for classifying monitored assets based on user labels and for detecting potential misuse of monitored assets based on the classifications | |
| US9317574B1 (en) | System and method for managing and identifying subject matter experts | |
| US8620875B2 (en) | Fraud analysis in a contact database | |
| US10169730B2 (en) | System and method to present a summarized task view in a case management system | |
| US20130006996A1 (en) | Clustering E-Mails Using Collaborative Information | |
| Japec et al. | AAPOR report on big data | |
| US10671926B2 (en) | Method and system for generating predictive models for scoring and prioritizing opportunities | |
| US10108616B2 (en) | Probabilistic link strength reduction | |
| US20160171590A1 (en) | Push-based category recommendations | |
| CN111191046A (en) | Method, device, computer storage medium and terminal for realizing information search | |
| CN109918678B (en) | Method and device for identifying field meaning | |
| Zhang et al. | Reputationpro: The efficient approaches to contextual transaction trust computation in e-commerce environments | |
| CN110728301A (en) | Credit scoring method, device, terminal and storage medium for individual user | |
| US20220138775A1 (en) | Systems and methods for computing engagement scores for record objects based on electronic activities and field-value pairs | |
| US8831969B1 (en) | System and method for determining users working for the same employers in a social network | |
| US10740536B2 (en) | Dynamic survey generation and verification | |
| US10733244B2 (en) | Data retrieval system | |
| US9525687B2 (en) | Template for customer attributes | |
| JP7278100B2 (en) | Post evaluation system and method | |
| CN111124990A (en) | Information technology service equipment | |
| CN111221978A (en) | Method and device for constructing knowledge graph, computer storage medium and terminal | |
| CN110930103A (en) | Service ticket checking method and system, medium and computer system | |
| CN115471274A (en) | Method, device, equipment and storage medium for establishing public and private linkage client label system | |
| CN114547406A (en) | Data monitoring method, system, storage medium and electronic device |
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 |