CN113177095A - Enterprise knowledge management method, system, electronic equipment and storage medium - Google Patents
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Abstract
The invention provides an enterprise knowledge management method, an enterprise knowledge management system, electronic equipment and a storage medium, wherein the technical scheme of the method comprises the steps of acquiring structured data in enterprise knowledge, carrying out first definition on contents needing mapping in the structured data, and generating a knowledge map according to the first definition on the contents needing mapping in the structured data; acquiring unstructured data in the enterprise knowledge, performing a second definition on contents needing mapping in the unstructured data, and supplementing the contents needing mapping in the unstructured data into the knowledge graph according to the second definition; setting the priority of the structured data and the unstructured data, and determining a coverage relation according to the priority when new content enters the knowledge graph; and constructing a visual interface, and visualizing and displaying the knowledge graph on the visual interface. The invention solves the problem that the prior method can not combine the two together for knowledge management.
Description
Technical Field
The invention belongs to the technical field of knowledge maps, and particularly relates to an enterprise knowledge management method, an enterprise knowledge management system, electronic equipment and a storage medium.
Background
The enterprise knowledge comprises an industry word stock, a dictionary stock, a rule stock, a model stock, industry consensus and the like, most of the knowledge is managed by adopting a hierarchical directory management mode, and the knowledge with different sources and different types faces challenges in updating, fusing and managing.
The existing knowledge management mainly adopts a hierarchical classification management mode, and combines various industry word banks, dictionary banks, rule banks, model banks and the like into a knowledge directory according to certain business logic, and stores data in a database for query. The method has the disadvantages of insufficient semantic expressive force, simple knowledge association and single dimension. The existing knowledge management based on the graph mainly focuses on the aspects of engineering structured knowledge extraction part and entity identification and extraction based on NLP technology, and a mechanism and a method for effectively combining the two parts together to carry out knowledge management are lacked.
Disclosure of Invention
The embodiment of the application provides an enterprise knowledge management method, an enterprise knowledge management system, electronic equipment and a storage medium, and aims to at least solve the problem that the existing enterprise knowledge management method cannot combine two parts together to perform knowledge management.
In a first aspect, an embodiment of the present application provides an enterprise knowledge management method, including: the method comprises the steps of structural data processing, namely acquiring structural data in enterprise knowledge, performing first definition on contents needing mapping in the structural data, and generating a knowledge map according to the first definition on the contents needing mapping in the structural data; the unstructured data processing step is that unstructured data in the enterprise knowledge are obtained, a second definition is carried out on the content needing to be mapped in the unstructured data, and the content needing to be mapped in the unstructured data is supplemented into the knowledge map according to the second definition; setting the priority of the structured data and the unstructured data, and determining a coverage relation according to the priority when new content enters the knowledge graph; and a visual interface construction step, namely constructing a visual interface, and visualizing and displaying the knowledge graph on the visual interface.
Preferably, the structured data processing step further comprises: analyzing the business field content in the structured data, and defining the entity, the relation category and the attribute in the business field content.
Preferably, the unstructured data processing step further comprises: analyzing the unstructured data through a natural language processing technology, constructing an extractor according to the second definition, extracting entities, relationship types and attributes in the unstructured data through the extractor, and supplementing the extracted entities, relationship types and attributes in the unstructured data into the knowledge graph.
Preferably, the method further comprises a knowledge-graph dynamic supplementation step: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
In a second aspect, an embodiment of the present application provides an enterprise knowledge management system, which is suitable for the above enterprise knowledge management method, and includes: the system comprises a structured data processing module, a knowledge graph generation module and a data processing module, wherein the structured data processing module is used for acquiring structured data in enterprise knowledge, performing first definition on contents needing to be mapped in the structured data, and generating the contents needing to be mapped in the structured data into the knowledge graph according to the first definition; the unstructured data processing module is used for acquiring unstructured data in the enterprise knowledge, performing second definition on contents needing mapping in the unstructured data, and supplementing the contents needing mapping in the unstructured data into the knowledge map according to the second definition; the priority strategy setting module is used for setting the priority of the structured data and the unstructured data, and when new content enters the knowledge graph, the coverage relation is determined according to the priority; and the visual interface construction module is used for constructing a visual interface, visualizing the knowledge graph and displaying the knowledge graph on the visual interface.
In some of these embodiments, the structured data processing module further comprises: analyzing the business field content in the structured data, and defining the entity, the relation category and the attribute in the business field content.
In some of these embodiments, the unstructured data processing module further comprises: analyzing the unstructured data through a natural language processing technology, constructing an extractor according to the second definition, extracting entities, relationship types and attributes in the unstructured data through the extractor, and supplementing the extracted entities, relationship types and attributes in the unstructured data into the knowledge graph.
In some embodiments, the system further comprises a knowledge-graph dynamic supplementation module: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
In a third aspect, an embodiment of the present application provides an electronic device, which includes a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the computer program, the processor implements an enterprise knowledge management method as described in the first aspect.
In a fourth aspect, the present application provides a computer-readable storage medium, on which a computer program is stored, which when executed by a processor implements an enterprise knowledge management method as described in the first aspect above.
The invention can be applied to the technical field of knowledge maps. Compared with the related technology, the embodiment of the application adopts an industry map library mode, makes full use of the abundant semantic expression capability of the map, and is more suitable for storing and managing basic knowledge with abundant types, different standards and various sources of enterprises. Specifically, the knowledge management based on the graph is carried out in a visual mode, so that the operation and threshold of the knowledge management are simplified; the method defines the process and the rule of the fusion operation of the atlas schema acquired by the structured data and the unstructured data acquisition schema, so that the knowledge acquired by multiple channels can be effectively fused on the mechanism, the logical limitation is increased, and the knowledge landform property is enhanced.
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The accompanying drawings, which are included to provide a further understanding of the application and are incorporated in and constitute a part of this application, illustrate embodiment(s) of the application and together with the description serve to explain the application and not to limit the application. In the drawings:
FIG. 1 is a flow chart of a method of enterprise knowledge management of the present invention;
FIG. 2 is a framework diagram of the enterprise knowledge management system of the present invention;
FIG. 3 is a block diagram of an electronic device of the present invention;
in the above figures:
1. a structured data processing module; 2. an unstructured data processing module; 3. a priority policy setting module; 4. a knowledge graph dynamic supplement module; 5. a visual interface construction module; 60. a bus; 61. a processor; 62. a memory; 63. a communication interface.
Detailed Description
In order to make the objects, technical solutions and advantages of the present application more apparent, the present application will be described and illustrated below with reference to the accompanying drawings and embodiments. It should be understood that the specific embodiments described herein are merely illustrative of the present application and are not intended to limit the present application. All other embodiments obtained by a person of ordinary skill in the art based on the embodiments provided in the present application without any inventive step are within the scope of protection of the present application.
It is obvious that the drawings in the following description are only examples or embodiments of the present application, and that it is also possible for a person skilled in the art to apply the present application to other similar contexts on the basis of these drawings without inventive effort. Moreover, it should be appreciated that in the development of any such actual implementation, as in any engineering or design project, numerous implementation-specific decisions must be made to achieve the developers' specific goals, such as compliance with system-related and business-related constraints, which may vary from one implementation to another.
Reference in the specification to "an embodiment" means that a particular feature, structure, or characteristic described in connection with the embodiment can be included in at least one embodiment of the specification. The appearances of the phrase in various places in the specification are not necessarily all referring to the same embodiment, nor are separate or alternative embodiments mutually exclusive of other embodiments. Those of ordinary skill in the art will explicitly and implicitly appreciate that the embodiments described herein may be combined with other embodiments without conflict.
Unless defined otherwise, technical or scientific terms referred to herein shall have the ordinary meaning as understood by those of ordinary skill in the art to which this application belongs. Reference to "a," "an," "the," and similar words throughout this application are not to be construed as limiting in number, and may refer to the singular or the plural. The present application is directed to the use of the terms "including," "comprising," "having," and any variations thereof, which are intended to cover non-exclusive inclusions; for example, a process, method, system, article, or apparatus that comprises a list of steps or modules (elements) is not limited to the listed steps or elements, but may include other steps or elements not expressly listed or inherent to such process, method, article, or apparatus.
According to the embodiment of the application, the knowledge in the enterprise is organized and managed in a map form, and entities, relations and events concerned by the business are defined.
Embodiments of the invention are described in detail below with reference to the accompanying drawings:
fig. 1 is a flowchart of an enterprise knowledge management method of the present invention, and referring to fig. 1, the enterprise knowledge management method of the present invention includes the following steps:
s1: acquiring structured data in enterprise knowledge, performing a first definition on contents needing to be mapped in the structured data, and generating a knowledge graph according to the first definition on the contents needing to be mapped in the structured data.
Optionally, the content of the service field in the structured data is analyzed, and the entity, the relationship category and the attribute in the content of the service field are defined.
In specific implementation, for structured data, by analyzing the content of a service field contained in a database table, the entities, the relationship types and the attributes which can be possessed by the entities and the relationship types included in part of the map are defined, and a map schema defined from the structured data is imported.
In the specific implementation, because the structured graph construction is a complex engineering logic, in order to ensure the high consistency of the work output result of the structured data graph generation and the management knowledge in the knowledge base, the schema defined by the structured data starting only supports incremental synchronization, and does not support the operations of deletion and modification.
S2: acquiring unstructured data in the enterprise knowledge, performing a second definition on contents needing mapping in the unstructured data, and supplementing the contents needing mapping in the unstructured data into the knowledge graph according to the second definition.
Optionally, the unstructured data is analyzed through a natural language processing technology, an extractor is constructed according to the second definition, entities, relationship categories and attributes in the unstructured data are extracted through the extractor, and the extracted entities, relationship categories and attributes in the unstructured data are supplemented into the knowledge graph.
In specific implementation, for unstructured data, an entity/relationship extractor is constructed through analysis of text data and comprehensive analysis of entity recognition algorithm capacity, so that supplement of map entities, relationship categories and attribute definitions is completed, and map schemas defined by unstructured data are synchronized in a knowledge map.
In a specific implementation, when the schema defined by the unstructured data is synchronized, if the schema is a brand-new schema, the identifier information is added into the original schema definition.
In the specific implementation, the manual adding, deleting and changing operations are supported for the map part with the source defined only by the unstructured data, and a user can add a new entity or modify an identifier associated with an original entity on a page according to the continuous enrichment and optimization of the identifier; for the schema with the source of both structured and unstructured parts, only the modification identifier is supported, and the deletion operation is not supported.
S3: and setting the priority of the structured data and the unstructured data, and determining the coverage relation according to the priority when new content enters the knowledge graph.
In a specific implementation, the setting of the data priority policy may select structured priority or unstructured priority, and data with high priority and low coverage priority may also be selected.
S4: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
In specific implementation, a knowledge extraction task supports timing and periodic execution, and structured data completes data addition by adopting an incremental operation mode; the unstructured data is updated by adopting a full-scale operation mode and a full-coverage strategy.
S5: and constructing a visual interface, and visualizing and displaying the knowledge graph on the visual interface.
FIG. 2 is a block diagram of an enterprise knowledge management system in accordance with the present invention, and referring to FIG. 2, including:
the structured data processing module 1: acquiring structured data in enterprise knowledge, performing a first definition on contents needing to be mapped in the structured data, and generating a knowledge graph according to the first definition on the contents needing to be mapped in the structured data.
Optionally, the content of the service field in the structured data is analyzed, and the entity, the relationship category and the attribute in the content of the service field are defined.
In specific implementation, for structured data, by analyzing the content of a service field contained in a database table, the entities, the relationship types and the attributes which can be possessed by the entities and the relationship types included in part of the map are defined, and a map schema defined from the structured data is imported.
In the specific implementation, because the structured graph construction is a complex engineering logic, in order to ensure the high consistency of the work output result of the structured data graph generation and the management knowledge in the knowledge base, the schema defined by the structured data starting only supports incremental synchronization, and does not support the operations of deletion and modification.
Unstructured data processing module 2: acquiring unstructured data in the enterprise knowledge, performing a second definition on contents needing mapping in the unstructured data, and supplementing the contents needing mapping in the unstructured data into the knowledge graph according to the second definition.
Optionally, the unstructured data is analyzed through a natural language processing technology, an extractor is constructed according to the second definition, entities, relationship categories and attributes in the unstructured data are extracted through the extractor, and the extracted entities, relationship categories and attributes in the unstructured data are supplemented into the knowledge graph.
In specific implementation, for unstructured data, an entity/relationship extractor is constructed through analysis of text data and comprehensive analysis of entity recognition algorithm capacity, so that supplement of map entities, relationship categories and attribute definitions is completed, and map schemas defined by unstructured data are synchronized in a knowledge map.
In a specific implementation, when the schema defined by the unstructured data is synchronized, if the schema is a brand-new schema, the identifier information is added into the original schema definition.
In the specific implementation, the manual adding, deleting and changing operations are supported for the map part with the source defined only by the unstructured data, and a user can add a new entity or modify an identifier associated with an original entity on a page according to the continuous enrichment and optimization of the identifier; for the schema with the source of both structured and unstructured parts, only the modification identifier is supported, and the deletion operation is not supported.
The priority policy setting module 3: and setting the priority of the structured data and the unstructured data, and determining the coverage relation according to the priority when new content enters the knowledge graph.
In a specific implementation, the setting of the data priority policy may select structured priority or unstructured priority, and data with high priority and low coverage priority may also be selected.
The knowledge graph dynamic supplement module 4: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
In specific implementation, a knowledge extraction task supports timing and periodic execution, and structured data completes data addition by adopting an incremental operation mode; the unstructured data is updated by adopting a full-scale operation mode and a full-coverage strategy.
The visual interface construction module 5: and constructing a visual interface, and visualizing and displaying the knowledge graph on the visual interface.
Additionally, one method of enterprise knowledge management described in connection with FIG. 1 may be implemented by an electronic device. Fig. 3 is a block diagram of an electronic device of the present invention.
The electronic device may comprise a processor 61 and a memory 62 in which computer program instructions are stored.
Specifically, the processor 61 may include a Central Processing Unit (CPU), or A Specific Integrated Circuit (ASIC), or may be configured to implement one or more Integrated circuits of the embodiments of the present Application.
The memory 62 may be used to store or cache various data files that need to be processed and/or used for communication, as well as possible computer program instructions executed by the processor 61.
The processor 61 implements any of the above-described embodiments of the enterprise knowledge management method by reading and executing computer program instructions stored in the memory 62.
In some of these embodiments, the electronic device may also include a communication interface 63 and a bus 60. As shown in fig. 3, the processor 61, the memory 62, and the communication interface 63 are connected via a bus 60 to complete communication therebetween.
The communication port 63 may be implemented with other components such as: the data communication is carried out among external equipment, image/data acquisition equipment, a database, external storage, an image/data processing workstation and the like.
The bus 60 includes hardware, software, or both to couple the components of the electronic device to one another. Bus 60 includes, but is not limited to, at least one of the following: data Bus (Data Bus), Address Bus (Address Bus), Control Bus (Control Bus), Expansion Bus (Expansion Bus), and Local Bus (Local Bus). By way of example, and not limitation, Bus 60 may include an Accelerated Graphics Port (AGP) or other Graphics Bus, an Enhanced Industry Standard Architecture (EISA) Bus, a Front-Side Bus (FSB), a Hyper Transport (HT) Interconnect, an ISA (ISA) Bus, an InfiniBand (InfiniBand) Interconnect, a Low Pin Count (LPC) Bus, a memory Bus, a microchannel Architecture (MCA) Bus, a PCI (Peripheral Component Interconnect) Bus, a PCI-Express (PCI-X) Bus, a Serial Advanced Technology Attachment (SATA) Bus, a Video Electronics Bus (audio Electronics Association), abbreviated VLB) bus or other suitable bus or a combination of two or more of these. Bus 60 may include one or more buses, where appropriate. Although specific buses are described and shown in the embodiments of the application, any suitable buses or interconnects are contemplated by the application.
The electronic device may perform a method for enterprise knowledge management in embodiments of the application.
In addition, in combination with the enterprise knowledge management method in the foregoing embodiments, the present application embodiment may provide a computer-readable storage medium to implement. The computer readable storage medium having stored thereon computer program instructions; the computer program instructions, when executed by a processor, implement any of the above-described embodiments of the enterprise knowledge management method.
And the aforementioned storage medium includes: various media capable of storing program codes, such as a usb disk, a removable hard disk, a Read Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk, or an optical disk.
The technical features of the embodiments described above may be arbitrarily combined, and for the sake of brevity, all possible combinations of the technical features in the embodiments described above are not described, but should be considered as being within the scope of the present specification as long as there is no contradiction between the combinations of the technical features.
The above-mentioned embodiments only express several embodiments of the present application, and the description thereof is more specific and detailed, but not construed as limiting the scope of the invention. It should be noted that, for a person skilled in the art, several variations and modifications can be made without departing from the concept of the present application, which falls within the scope of protection of the present application. Therefore, the protection scope of the present patent shall be subject to the appended claims.
Claims (10)
1. An enterprise knowledge management method, comprising:
the method comprises the steps of structural data processing, namely acquiring structural data in enterprise knowledge, performing first definition on contents needing mapping in the structural data, and generating a knowledge map according to the first definition on the contents needing mapping in the structural data;
the unstructured data processing step is that unstructured data in the enterprise knowledge are obtained, a second definition is carried out on the content needing to be mapped in the unstructured data, and the content needing to be mapped in the unstructured data is supplemented into the knowledge map according to the second definition;
setting the priority of the structured data and the unstructured data, and determining a coverage relation according to the priority when new content enters the knowledge graph;
and a visual interface construction step, namely constructing a visual interface, and visualizing and displaying the knowledge graph on the visual interface.
2. The enterprise knowledge management method of claim 1, wherein the structured data processing step further comprises: analyzing the business field content in the structured data, and defining the entity, the relation category and the attribute in the business field content.
3. The enterprise knowledge management method of claim 1, wherein the unstructured data processing step further comprises: analyzing the unstructured data through a natural language processing technology, constructing an extractor according to the second definition, extracting entities, relationship types and attributes in the unstructured data through the extractor, and supplementing the extracted entities, relationship types and attributes in the unstructured data into the knowledge graph.
4. The method for enterprise knowledge management of claim 1, the method further comprising a knowledge-graph dynamic supplementation step: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
5. An enterprise knowledge management system, comprising:
the system comprises a structured data processing module, a knowledge graph generation module and a data processing module, wherein the structured data processing module is used for acquiring structured data in enterprise knowledge, performing first definition on contents needing to be mapped in the structured data, and generating the contents needing to be mapped in the structured data into the knowledge graph according to the first definition;
the unstructured data processing module is used for acquiring unstructured data in the enterprise knowledge, performing second definition on contents needing mapping in the unstructured data, and supplementing the contents needing mapping in the unstructured data into the knowledge map according to the second definition;
the priority strategy setting module is used for setting the priority of the structured data and the unstructured data, and when new content enters the knowledge graph, the coverage relation is determined according to the priority;
and the visual interface construction module is used for constructing a visual interface, visualizing the knowledge graph and displaying the knowledge graph on the visual interface.
6. The enterprise knowledge management system of claim 5, wherein the structured data processing module further comprises: analyzing the business field content in the structured data, and defining the entity, the relation category and the attribute in the business field content.
7. The enterprise knowledge management system of claim 5, wherein the unstructured data processing module further comprises: analyzing the unstructured data through a natural language processing technology, constructing an extractor according to the second definition, extracting entities, relationship types and attributes in the unstructured data through the extractor, and supplementing the extracted entities, relationship types and attributes in the unstructured data into the knowledge graph.
8. The enterprise knowledge management system of claim 5, wherein the system further comprises a knowledge-graph dynamic supplementation module: and supplementing the knowledge graph according to a preset period, supplementing the structured data in an incremental operation mode, and supplementing the unstructured data in a full operation mode.
9. An electronic device comprising a memory, a processor, and a computer program stored on the memory and executable on the processor, wherein the processor implements the enterprise knowledge management method of any of claims 1-4 when executing the computer program.
10. A computer-readable storage medium, on which a computer program is stored, which, when being executed by a processor, carries out the enterprise knowledge management method according to any one of claims 1 to 4.
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Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592448A (en) * | 2021-07-29 | 2021-11-02 | 上海明略人工智能(集团)有限公司 | Internet product archive management method, system, electronic equipment and storage medium |
| CN113849579A (en) * | 2021-09-27 | 2021-12-28 | 支付宝(杭州)信息技术有限公司 | Knowledge graph data processing method and system based on knowledge view |
| CN114943001A (en) * | 2022-07-26 | 2022-08-26 | 风蝶科技文化(深圳)有限公司 | Enterprise knowledge informatization management method and system |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107330125A (en) * | 2017-07-20 | 2017-11-07 | 云南电网有限责任公司电力科学研究院 | The unstructured distribution data integrated approach of magnanimity of knowledge based graphical spectrum technology |
| US20190164063A1 (en) * | 2017-11-28 | 2019-05-30 | International Business Machines Corporation | Data classification |
| CN110245241A (en) * | 2019-06-18 | 2019-09-17 | 卓尔智联(武汉)研究院有限公司 | Plastics knowledge mapping construction device, method and computer readable storage medium |
| CN110750650A (en) * | 2019-09-30 | 2020-02-04 | 中盈优创资讯科技有限公司 | Construction method and device of enterprise knowledge graph |
| CN112612899A (en) * | 2020-11-24 | 2021-04-06 | 中国传媒大学 | Knowledge graph construction method and device, storage medium and electronic equipment |
-
2021
- 2021-04-29 CN CN202110471754.5A patent/CN113177095A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107330125A (en) * | 2017-07-20 | 2017-11-07 | 云南电网有限责任公司电力科学研究院 | The unstructured distribution data integrated approach of magnanimity of knowledge based graphical spectrum technology |
| US20190164063A1 (en) * | 2017-11-28 | 2019-05-30 | International Business Machines Corporation | Data classification |
| CN110245241A (en) * | 2019-06-18 | 2019-09-17 | 卓尔智联(武汉)研究院有限公司 | Plastics knowledge mapping construction device, method and computer readable storage medium |
| CN110750650A (en) * | 2019-09-30 | 2020-02-04 | 中盈优创资讯科技有限公司 | Construction method and device of enterprise knowledge graph |
| CN112612899A (en) * | 2020-11-24 | 2021-04-06 | 中国传媒大学 | Knowledge graph construction method and device, storage medium and electronic equipment |
Cited By (3)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN113592448A (en) * | 2021-07-29 | 2021-11-02 | 上海明略人工智能(集团)有限公司 | Internet product archive management method, system, electronic equipment and storage medium |
| CN113849579A (en) * | 2021-09-27 | 2021-12-28 | 支付宝(杭州)信息技术有限公司 | Knowledge graph data processing method and system based on knowledge view |
| CN114943001A (en) * | 2022-07-26 | 2022-08-26 | 风蝶科技文化(深圳)有限公司 | Enterprise knowledge informatization management method and system |
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