CN112905612A - Knowledge card construction method and device - Google Patents
Knowledge card construction method and device Download PDFInfo
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- CN112905612A CN112905612A CN202110167514.6A CN202110167514A CN112905612A CN 112905612 A CN112905612 A CN 112905612A CN 202110167514 A CN202110167514 A CN 202110167514A CN 112905612 A CN112905612 A CN 112905612A
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- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/23—Updating
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- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/28—Databases characterised by their database models, e.g. relational or object models
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Abstract
The invention provides a construction method and a device of a knowledge card, wherein the method comprises the following steps: acquiring at least one piece of original data from an original database; determining at least one first triple information of the current original data aiming at each piece of original data in at least one piece of original data, wherein each first triple information comprises two entities, a relationship between the two entities or entity attribute information; generating an ontology base of the knowledge graph to be constructed according to the first triple information; generating a knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed; generating a knowledge card to be constructed according to the knowledge graph to be constructed; when it is monitored that a newly added original data exists in the original database, determining at least one newly added first triple information of the newly added original data, and updating the ontology base; and updating the knowledge card to be constructed according to the updated ontology base. The intelligent degree that knowledge card found can be improved to this scheme.
Description
Technical Field
The invention relates to the technical field of computers, in particular to a method and a device for constructing a knowledge card.
Background
With the continuous development of the mobile internet, mobile learning becomes a learning mode which is widely selected by learners at present. In the face of the problems in fragmented learning, learners need to manage knowledge urgently, so knowledge cards are produced at the same time.
In the prior art, visual knowledge cards are generally generated according to suggestions of different data display effects and by combining with the specific form of a visual chart. However, the intelligence level of the prior art knowledge card construction is low.
Disclosure of Invention
The embodiment of the invention provides a method and a device for constructing a knowledge card, which can improve the intelligent degree of the construction of the knowledge card.
In a first aspect, an embodiment of the present invention provides a method for constructing a knowledge card, where the method includes:
acquiring at least one piece of original data from an original database;
determining at least one first triple information of the current original data aiming at each piece of original data in the at least one piece of original data, wherein each first triple information comprises two entities, a relation between the two entities or entity attribute information;
generating an ontology base of the knowledge graph to be constructed according to the first triple information;
generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed;
generating the knowledge card to be constructed according to the knowledge graph to be constructed;
when it is monitored that one piece of newly added original data exists in the original database, determining at least one newly added first triple information of the newly added original data;
updating the ontology base according to the at least one newly added first triple information;
updating the knowledge graph to be constructed according to the updated ontology base;
and updating the knowledge card to be constructed according to the updated knowledge graph to be constructed.
Preferably, the first and second electrodes are formed of a metal,
the at least one piece of raw data includes: structured raw data, semi-structured raw data and unstructured raw data;
the determining, for each piece of raw data of the at least one piece of raw data, at least one first triplet information in the current raw data includes:
d1: determining whether the current original data is the structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured raw data as a first triplet of information;
d3: determining whether the current raw data is the semi-structured raw data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: taking the analyzed current original data as the first triple information;
d6: determining whether the current raw data is unstructured raw data;
d7: and when the current original data is determined to be the unstructured original data, extracting one first triple information in the current original data.
Preferably, the first and second electrodes are formed of a metal,
the generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed comprises the following steps:
taking two entities contained in each first triple as two nodes of the knowledge graph to be constructed respectively, wherein the two entities have the same definition as the entities in the knowledge graph to be constructed;
taking the relationship or entity attribute information between the two entities contained in each first triple as an edge of the to-be-constructed knowledge graph, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the to-be-constructed knowledge graph;
and generating a knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
Preferably, the first and second electrodes are formed of a metal,
the knowledge card to be constructed comprises: at least one card element;
and the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph.
The generating the knowledge card to be constructed according to the knowledge graph to be constructed comprises the following steps:
determining a target template of the knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing the card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating the card to be constructed according to the target hyperlink and the target template.
Preferably, the first and second electrodes are formed of a metal,
generating an ontology base of the knowledge graph to be constructed according to the first triple information, wherein the generating comprises:
constructing a mode layer of a knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, wherein the mode layer of the knowledge graph comprises at least one second triple information, each second triple information comprises two ontologies, a relation between the two ontologies or ontology attribute information, the two entities are instances corresponding to the two ontologies, and the data layer of the knowledge graph comprises the at least one first triple information;
and generating the ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
In a second aspect, an embodiment of the present invention provides a knowledge card constructing apparatus, including:
the acquisition module is used for acquiring at least one piece of original data from an original database;
a determining module, configured to determine, for each piece of raw data in the at least one piece of raw data acquired by the acquiring module, at least one first triple information of the current raw data, where each first triple information includes two entities, a relationship between the two entities, or entity attribute information;
constructing a module: generating an ontology base of the knowledge graph to be constructed according to the first triple information determined by the determining module; generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed; generating the knowledge card to be constructed according to the knowledge graph to be constructed;
an update module: the method comprises the steps of determining at least one newly added first triple information of newly added original data when it is monitored that one piece of newly added original data exists in the original database; updating the ontology base according to the at least one newly added first triple information; updating the knowledge graph to be constructed according to the updated ontology base; and updating the knowledge card to be constructed according to the updated knowledge graph to be constructed.
Preferably, the first and second electrodes are formed of a metal,
the at least one piece of raw data includes: structured raw data, semi-structured raw data and unstructured raw data;
the determining module is configured to perform:
d1: determining whether the current original data is the structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured raw data as a first triplet of information;
d3: determining whether the current raw data is the semi-structured raw data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: taking the analyzed current original data as the first triple information;
d6: determining whether the current raw data is unstructured raw data;
d7: and when the current original data is determined to be the unstructured original data, extracting one first triple information in the current original data.
Preferably, the first and second electrodes are formed of a metal,
the construction module is configured to use two entities included in each of the first triples as two nodes of the to-be-constructed knowledge graph respectively, where the two entities are defined the same as entities in the to-be-constructed knowledge graph; taking the relationship or entity attribute information between the two entities contained in each first triple as an edge of the to-be-constructed knowledge graph, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the to-be-constructed knowledge graph; and generating a knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
Preferably, the first and second electrodes are formed of a metal,
the knowledge card to be constructed comprises: at least one card element;
and the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph.
The building module is further configured to perform:
determining a target template of the knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing the card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating the card to be constructed according to the target hyperlink and the target template.
Preferably, the first and second electrodes are formed of a metal,
the building module is further configured to build a mode layer of a knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, where the mode layer of the knowledge graph includes at least one second triple information, each second triple information includes two ontologies, a relationship between the two ontologies, or ontology attribute information, the two entities are instances corresponding to the two ontologies, and the data layer of the knowledge graph includes the at least one first triple information; and generating the ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
The embodiment of the invention provides a method and a device for constructing a knowledge card, wherein a knowledge graph is a graph for describing a knowledge development process and displaying a knowledge structure relationship, fragmented knowledge can be managed based on a knowledge graph technology, and the fragmented knowledge is formed into a knowledge system of a learner by constructing the association between the knowledge. Therefore, the knowledge graph to be constructed is the key for forming the knowledge card to be constructed. For the construction of the knowledge graph, the ontology base of the knowledge graph to be constructed can be generated by determining the first triple information of each piece of original data in the original database, based on two entities contained in each piece of first triple information, the relationship between the two entities or the entity attribute information, and the knowledge graph to be constructed can be further generated, and meanwhile, the knowledge card to be constructed can be formed based on the knowledge graph to be constructed. The automatic updating of the knowledge graph to be constructed can realize the automatic updating of the knowledge card to be constructed. By the above mode, the knowledge card to be constructed is generated based on the knowledge map to be constructed, and meanwhile, the intelligence degree of the knowledge card to be constructed can be improved by continuously perfecting and updating.
Drawings
In order to more clearly illustrate the embodiments of the present invention or the technical solutions in the prior art, the drawings used in the description of the embodiments or the prior art will be briefly introduced below, and it is obvious that the drawings in the following description are some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to these drawings without creative efforts.
FIG. 1 is a flow chart of a method for constructing a knowledge card according to an embodiment of the present invention;
FIG. 2 is a flow chart of another method for constructing a knowledge card according to an embodiment of the invention;
fig. 3 is a schematic diagram of a knowledge card constructing apparatus according to an embodiment of the present invention.
Detailed Description
In order to make the objects, technical solutions and advantages of the embodiments of the present invention clearer and more complete, the technical solutions in the embodiments of the present invention will be described below with reference to the drawings in the embodiments of the present invention, and it is obvious that the described embodiments are some, but not all, embodiments of the present invention, and based on the embodiments of the present invention, all other embodiments obtained by a person of ordinary skill in the art without creative efforts belong to the scope of the present invention.
As shown in fig. 1, an embodiment of the present invention provides a method for constructing a knowledge card, which may include the following steps:
step 101: acquiring at least one piece of original data from an original database;
step 102: determining at least one first triple information of the current original data aiming at each piece of original data in at least one piece of original data, wherein each first triple information comprises two entities, a relationship between the two entities or entity attribute information;
step 103: generating an ontology base of the knowledge graph to be constructed according to the first triple information;
step 104: generating a knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed;
step 105: generating a knowledge card to be constructed according to the knowledge graph to be constructed;
step 106: when it is monitored that a newly added original data exists in the original database, determining at least one newly added first triple information of the newly added original data;
step 107: updating the ontology base according to at least one newly added first triple information;
step 108: updating the knowledge graph to be constructed according to the updated ontology base;
step 109: and updating the knowledge card to be constructed according to the updated knowledge map to be constructed.
In the embodiment of the invention, the knowledge graph is a graph for describing the knowledge development process and displaying the knowledge structure relationship, fragmented knowledge can be managed based on the knowledge graph technology, and the fragmented knowledge is formed into a knowledge system of a learner by constructing the association between the knowledge. Therefore, the knowledge graph to be constructed is the key for forming the knowledge card to be constructed. For the construction of the knowledge graph, the ontology base of the knowledge graph to be constructed can be generated by determining the first triple information of each piece of original data in the original database, based on two entities contained in each piece of first triple information, the relationship between the two entities or the entity attribute information, and the knowledge graph to be constructed can be further generated, and meanwhile, the knowledge card to be constructed can be formed based on the knowledge graph to be constructed. The automatic updating of the knowledge graph to be constructed can realize the automatic updating of the knowledge card to be constructed. By the above mode, the knowledge card to be constructed is generated based on the knowledge map to be constructed, and meanwhile, the intelligence degree of the knowledge card to be constructed can be improved by continuously perfecting and updating.
For data processing, in an embodiment of the present invention, at least one piece of original data in the above embodiment includes: structured raw data, semi-structured raw data and unstructured raw data;
step 102 in the foregoing embodiment may be specifically implemented as follows:
d1: determining whether the current original data is structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured original data as a first triple information;
d3: determining whether the current original data is semi-structured original data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: using the analyzed current original data as a first triple information;
d6: determining whether the current original data is unstructured original data;
d7: when the current original data is determined to be unstructured original data, extracting a first triple information in the current original data.
In the embodiment of the present invention, the original data may be divided into: structured raw data, semi-structured raw data, and unstructured raw data. Different methods may be employed to convert the raw data into the form of the first triplet, depending on the different structured form of the raw data. For example, for structured raw data, which is usually data of a relational database, the data structure is clear, the raw data in the relational database can be converted into RDF data, generally adopting D2R technology, D2R mainly includes D2R Server, D2RQ Engine and D2RRQ Mapping languages; the semi-structured raw data mainly refers to data which has a certain data structure and needs to be further extracted and sorted. Such as encyclopedia data, data in web pages, etc. For the data, a wrapper mode is mainly adopted for processing; for unstructured raw data, knowledge extraction including entities, entity relationships, and specific entity attributes is required.
In order to generate the knowledge graph to be constructed, in an embodiment of the present invention, step 104 in the above embodiment may be specifically implemented by:
respectively taking two entities contained in each first triple as two nodes of the knowledge graph to be constructed, wherein the two entities are defined as the same as the entities in the knowledge graph to be constructed;
taking the relationship or entity attribute information between two entities contained in each first triple as an edge of the knowledge graph to be constructed, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the knowledge graph to be constructed;
and generating the knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
In an embodiment of the invention, a knowledge graph is a graph formed by nodes and edges that reflects the structure of knowledge, in the knowledge graph, nodes represent entities, edges represent relationships between the entities, and the first three-element information comprises two entities, a relationship between the two entities and attributes of a specific entity, so that the two entities, the relationship between the two entities and the attributes of the specific entity in the first three-element information can be mapped to each node and edge of the knowledge graph, in this process, the entity definitions, attribute definitions and relationship definitions in the first triplet information and the knowledge-graph must remain consistent, and providing a basis for mapping the two entities contained in the first triple information, the relationship between the two entities and the attribute of the specific entity to the corresponding nodes and edges in the knowledge graph, thereby generating the knowledge graph to be constructed.
In order to generate a knowledge card to be constructed, in an embodiment of the present invention, the knowledge card to be constructed in the above embodiment includes: at least one card element;
the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph.
Step 105 in the above embodiment generates a knowledge card to be constructed according to the knowledge graph to be constructed, which may be specifically implemented as follows:
determining a target template of a knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating a card to be constructed according to the target hyperlink and the target template.
In the embodiment of the invention, the knowledge card comprises at least one card element, a finally displayed card to be constructed needs to be generated based on the construction of the at least one card element and the construction of the model integrally displayed by the whole knowledge card, a chart library comprising a broken line chart, a pie chart, a bubble chart, a radar chart and a relation chart can be set for each card element, so that the card to be constructed can be visually displayed in a chart mode, meanwhile, a target template of the knowledge card to be constructed can be determined from a preset model library, a target hyperlink can be added to the target card element needing to be associated with the knowledge map to be constructed, so that when the target card element is triggered, the knowledge card to be constructed can jump to the associated knowledge map to be constructed, the association relationship between the knowledge map to be constructed and the knowledge card to be constructed is realized, and the dynamic update of the knowledge card to be constructed can be realized based on the dynamic update of the knowledge card to be constructed.
In order to generate the ontology base of the knowledge graph to be constructed, in an embodiment of the present invention, in step 103 in the above embodiment, the ontology base of the knowledge graph to be constructed is generated according to the first triple information, which may specifically be implemented in the following manner:
according to at least one first triple information in each piece of original data, a mode layer of the knowledge graph and a data layer of the knowledge graph are constructed, wherein the mode layer of the knowledge graph comprises at least one second triple information, each second triple information comprises two bodies, a relation between the two bodies or body attribute information, the two bodies are corresponding examples of the two bodies, and the data layer of the knowledge graph comprises at least one first triple information;
and generating an ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
In the embodiment of the invention, each triplet information contains two entities, the relationship between the two entities and the attribute of a specific entity, so that the knowledge graph to be constructed can be generated based on each first triplet information. In the construction process of the knowledge graph to be constructed, a mode layer of the knowledge graph and a data layer of the knowledge graph can be constructed firstly based on at least one first triple information in each piece of original data, so that an ontology base of the knowledge graph to be constructed can be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph, and the knowledge graph to be constructed can be generated conveniently.
In one embodiment of the invention, the domain knowledge graph for automatic learning is constructed by the domain knowledge graph technology based on internet data and basic knowledge base data, and the domain knowledge card is formed by combining the visual display technology, so that a technical means for rapidly learning and mastering knowledge is provided for a user. The knowledge graph technology is mainly promoted to exert the abilities of managing information, associating knowledge and forming a system when facing the appeals of learners to knowledge mastery in different fields, so that a set of automatic construction method and equipment are formed, the requirements of knowledge card construction in different scenes are met, and meanwhile, visual display equipment is utilized to provide visual and convenient browsing modes for learners.
In an embodiment of the invention, the method can be applied to knowledge construction and knowledge card construction of hot events, analysis and mining are carried out by collecting real-time event data, a knowledge base and a knowledge map are generated by natural language processing and machine learning technologies, the knowledge card is automatically created and pushed by automatic analysis and management, and actual administrative managers of the hot events master the condition of one hand, are quickly associated, know the situation and assist in decision making. And constructing a hot event knowledge graph, describing from each attribute of the event, establishing an incidence relation between different events, and constructing a function construction application example through a knowledge card to provide knowledge service for a user. Different hot events may create different cards to show in different topics.
As shown in fig. 2, in order to explain the technical solution of the present invention in more detail, an embodiment of the present invention provides a method for constructing a knowledge card, including:
step 201: obtaining at least one piece of raw data from a raw database, wherein the at least one piece of raw data comprises: structured raw data, semi-structured raw data, and unstructured raw data.
Specifically, the original data can obtain multi-source data of the public safety field from the internet, a basic knowledge base and a professional database, can be applied to services of knowledge learning and mining oriented to the public safety field, including public opinion monitoring, hotspot tracking, actor-related emotion tendency analysis and the like, automatically obtains latest network information data through a network crawler, dynamically updates and expands the existing knowledge base by applying knowledge map automatic construction technology, and provides knowledge support for behavior analysis of the public safety field.
For example, the original data was assumed to be that Zhang III in 1992 steals an Audi car in a great wall building.
Step 202: and determining whether the current original data is structured original data, if so, executing step 203, otherwise, executing step 204.
Step 203: determining the structured original data as a first triple information, wherein each first triple information includes two entities, a relationship between the two entities, or entity attribute information, and performing step 208.
Step 204: and (4) determining whether the current raw data is semi-structured raw data, if so, executing the step 205, otherwise, executing the step 206.
Step 205: and analyzing the current original data, taking the analyzed current original data as a first triple information, and executing step 208.
Step 206: it is determined whether the current raw data is unstructured raw data.
Step 207: when the current original data is determined to be unstructured original data, a first triple information in the current original data is extracted, and step 208 is executed.
Specifically, entity recognition is carried out on multi-source data in the public security field, and named entity recognition is a basic and important processing link of natural language processing. Named entity recognition directly determines the accuracy of subsequent data. And (4) performing relation extraction on the public safety field multi-source data after entity identification, wherein the relation extraction is used as an important link for establishing the knowledge graph, and the data quality of the knowledge graph establishment is directly determined. The model that can be used for the relationship extraction is: the system comprises a BERT + bidirectional GRU + an Attention + FC, wherein the BERT is used for extracting the characteristics of a text, the Attention is an Attention mechanism layer, the FC is a knowledge description of a full-link layer knowledge overview, and is encyclopedic-like knowledge description, and data indexes of all entities can be inquired, intelligent matching recommendation is realized through a recommendation algorithm, and the like.
For example, based on the above analysis, the raw data is unstructured raw data, and at least one triplet needs to be extracted, assuming that the data is a three-in-one theft-in great wall building; zhangsan-age-1992.
Step 208: and constructing a mode layer of the knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, wherein the mode layer of the knowledge graph comprises at least one second triple information, each second triple information comprises two bodies, a relation between the two bodies or body attribute information, the two bodies are corresponding examples of the two bodies, and the data layer of the knowledge graph comprises at least one first triple information.
For example, the mode layer is: name-event-location; name-age-time;
the data layer is: zhang III-stealing-great wall mansion; zhangsan-age-1992.
Step 209: and generating an ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
In particular, the ontology library includes a collection of data describing domain knowledge. The method specifically comprises five basic constituent elements of concepts, relations, functions, axioms and examples. The method comprises the following steps of constructing an ontology, wherein the ontology is mainly divided into a plurality of parts, and the professional field, the scope and the application target covered by the ontology are determined; secondly, enumerating all concepts in the field and explaining the concepts in detail; thirdly, establishing a classification concept and a hierarchy of the classification concept; and fourthly, defining the relationship between the concepts.
Step 210: respectively taking two entities contained in each first triple as two nodes of the knowledge graph to be constructed, wherein the two entities are defined as the same as the entities in the knowledge graph to be constructed;
step 211: and taking the relationship or entity attribute information between the two entities contained in each first triple as the edge of the knowledge graph to be constructed, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the knowledge graph to be constructed.
Step 212: and generating the knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
Specifically, a knowledge base is formed through the construction of ontology knowledge, and the knowledge base is stored in the form of a graph database.
For example, taking the second triad of name-event-location as an example, the nodes are name and location, and the edges are events, that is, Zhang III and great wall building are nodes, and stealing is edge, the most basic knowledge graph can be generated to reflect the relationship between Zhang III and great wall building.
Step 213: determining a target template of a knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed, and the knowledge card to be constructed comprises: the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph.
Step 214: determining target card elements in the card to be constructed, wherein the target card elements are used for representing card elements needing to be associated with the knowledge graph to be constructed;
step 215: and adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed.
Step 216: and generating a card to be constructed according to the target hyperlink and the target template.
Specifically, the knowledge graph data can be utilized, and the visual knowledge card to be constructed can be automatically generated according to suggestions of different data display effects and by combining the specific form of the visual chart. When the knowledge card to be constructed is constructed, data can be bound with a display page of a foreground, a target hyperlink can be added to the display page according to the relation between the knowledge point and other knowledge points, and a user can browse various kinds of knowledge through continuous click. Meanwhile, the knowledge cards to be constructed can be displayed for users through visual display equipment, the knowledge cards to be constructed are displayed in modes of APP, webpages and the like, the knowledge maps to be constructed are automatically associated, the relationship among the knowledge points is displayed, and the knowledge maps are displayed in a map form.
For example, the method can be presented in a B/S architecture and a Web page mode, and the construction process can be automated, and can also be manually intervened and interactively designed.
Step 217: and when it is monitored that a newly added original data exists in the original database, determining at least one newly added first triple information of the newly added original data.
Step 218: updating the ontology base according to at least one newly added first triple information; updating the knowledge graph to be constructed according to the updated ontology base; and updating the knowledge card to be constructed according to the updated knowledge map to be constructed.
As shown in fig. 3, an embodiment of the present invention provides a knowledge card constructing apparatus, including:
an obtaining module 301, configured to obtain at least one piece of raw data from a raw database;
a determining module 302, configured to determine, for each piece of raw data in the at least one piece of raw data acquired by the acquiring module 301, at least one first triple information of the current raw data, where each first triple information includes two entities, a relationship between the two entities, or entity attribute information;
the building module 303: generating an ontology base of the knowledge graph to be constructed according to the first triple information determined 302 by the determining module; generating a knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed; generating a knowledge card to be constructed according to the knowledge graph to be constructed;
the update module 304: the method comprises the steps of determining at least one newly added first triple information of newly added original data when it is monitored that one newly added original data exists in an original database; updating the ontology base according to at least one newly added first triple information; updating the knowledge graph to be constructed, which is obtained by processing of the construction module 303, according to the updated ontology base; and updating the knowledge card to be constructed according to the updated knowledge map to be constructed.
In the embodiment of the invention, the knowledge graph is a graph for describing the knowledge development process and displaying the knowledge structure relationship, fragmented knowledge can be managed based on the knowledge graph technology, and the fragmented knowledge is formed into a knowledge system of a learner by constructing the association between the knowledge. Therefore, the knowledge graph to be constructed is the key for forming the knowledge card to be constructed. For the construction of the knowledge graph, the first triple information of each piece of original data in the original database acquired by the acquisition module can be determined by the determination module, the ontology base of the knowledge graph to be constructed is generated by the construction module based on two entities contained in each piece of first triple information, the relationship between the two entities or the entity attribute information, and the knowledge graph to be constructed is further generated, and meanwhile, the knowledge graph to be constructed can be formed based on the knowledge graph to be constructed. The automatic updating of the knowledge graph to be constructed can realize the automatic updating of the knowledge card to be constructed through the updating module. By the above mode, the knowledge card to be constructed is generated based on the knowledge map to be constructed, and meanwhile, the intelligence degree of the knowledge card to be constructed can be improved by continuously perfecting and updating.
In an embodiment of the present invention, the at least one piece of raw data includes: structured raw data, semi-structured raw data and unstructured raw data;
a determining module 302 configured to perform:
d1: determining whether the current original data is structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured original data as a first triple information;
d3: determining whether the current original data is semi-structured original data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: using the analyzed current original data as a first triple information;
d6: determining whether the current original data is unstructured original data;
d7: when the current original data is determined to be unstructured original data, extracting a first triple information in the current original data.
In an embodiment of the present invention, the construction module is configured to use two entities included in each first triple as two nodes of the to-be-constructed knowledge graph, respectively, where the two entities are defined the same as the entities in the to-be-constructed knowledge graph; taking the relationship or entity attribute information between two entities contained in each first triple as an edge of the knowledge graph to be constructed, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the knowledge graph to be constructed; and generating the knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
In an embodiment of the invention, the knowledge card to be constructed comprises: at least one card element;
the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph.
A building module 303 further configured to perform:
determining a target template of a knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating a card to be constructed according to the target hyperlink and the target template.
In an embodiment of the present invention, the constructing module 303 is further configured to construct a mode layer of the knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, where the mode layer of the knowledge graph includes at least one second triple information, each second triple information includes two ontologies, a relationship between the two ontologies, or ontology attribute information, the two entities are instances corresponding to the two ontologies, and the data layer of the knowledge graph includes at least one first triple information; and generating an ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
It is to be understood that the illustrated structure of the embodiment of the present invention does not specifically limit the knowledge-graph constructing apparatus. In other embodiments of the invention, the knowledge-graph constructing apparatus may include more or fewer components than shown, or some components may be combined, some components may be split, or a different arrangement of components may be used. The illustrated components may be implemented in hardware, software, or a combination of software and hardware.
Because the information interaction, execution process, and other contents between the units in the device are based on the same concept as the method embodiment of the present invention, specific contents may refer to the description in the method embodiment of the present invention, and are not described herein again.
The embodiment of the invention also provides a device for constructing the knowledge graph, which comprises the following steps: at least one memory and at least one processor;
at least one memory for storing a machine readable program;
at least one processor for invoking a machine readable program to perform a method of constructing a knowledge graph according to any embodiment of the invention.
Embodiments of the present invention further provide a computer-readable medium, on which computer instructions are stored, and when executed by a processor, the computer instructions cause the processor to execute the method for constructing a knowledge graph according to any embodiment of the present invention.
Specifically, a system or an apparatus equipped with a storage medium on which software program codes that realize the functions of any of the above-described embodiments are stored may be provided, and a computer (or a CPU or MPU) of the system or the apparatus is caused to read out and execute the program codes stored in the storage medium.
In this case, the program code itself read from the storage medium can realize the functions of any of the above-described embodiments, and thus the program code and the storage medium storing the program code constitute a part of the present invention.
Examples of the storage medium for supplying the program code include a floppy disk, a hard disk, a magneto-optical disk, an optical disk (e.g., CD-ROM, CD-R, CD-RW, DVD-ROM, DVD-RAM, DVD-RW, DVD + RW), a magnetic tape, a nonvolatile memory card, and a ROM. Alternatively, the program code may be downloaded from a server computer via a communications network.
Further, it should be clear that the functions of any one of the above-described embodiments may be implemented not only by executing the program code read out by the computer, but also by causing an operating system or the like operating on the computer to perform a part or all of the actual operations based on instructions of the program code.
Further, it is to be understood that the program code read out from the storage medium is written to a memory provided in an expansion board inserted into the computer or to a memory provided in an expansion unit connected to the computer, and then causes a CPU or the like mounted on the expansion board or the expansion unit to perform part or all of the actual operations based on instructions of the program code, thereby realizing the functions of any of the above-described embodiments.
The embodiments of the invention have at least the following beneficial effects:
1. in the embodiment of the invention, the knowledge graph is a graph for describing the knowledge development process and displaying the knowledge structure relationship, fragmented knowledge can be managed based on the knowledge graph technology, and the fragmented knowledge is formed into a knowledge system of a learner by constructing the association between the knowledge. Therefore, the knowledge graph to be constructed is the key for forming the knowledge card to be constructed. For the construction of the knowledge graph, the ontology base of the knowledge graph to be constructed can be generated by determining the first triple information of each piece of original data in the original database, based on two entities contained in each piece of first triple information, the relationship between the two entities or the entity attribute information, and the knowledge graph to be constructed can be further generated, and meanwhile, the knowledge card to be constructed can be formed based on the knowledge graph to be constructed. The automatic updating of the knowledge graph to be constructed can realize the automatic updating of the knowledge card to be constructed. By the method, the knowledge card to be constructed is generated based on the knowledge map to be constructed, and meanwhile, the intelligence degree of the construction of the knowledge card to be constructed can be improved by continuously perfecting and updating;
2. in an embodiment of the present invention, the original data may be divided into: structured raw data, semi-structured raw data, and unstructured raw data. Different methods may be employed to convert the raw data into the form of the first triplet, depending on the different structured form of the raw data. For example, for structured raw data, which is usually data of a relational database, the data structure is clear, the raw data in the relational database can be converted into RDF data, generally adopting D2R technology, D2R mainly includes D2R Server, D2RQ Engine and D2RRQ Mapping languages; the semi-structured raw data mainly refers to data which has a certain data structure and needs to be further extracted and sorted. Such as encyclopedia data, data in web pages, etc. For the data, a wrapper mode is mainly adopted for processing; for unstructured raw data, knowledge extraction including entities, entity relationships and specific entity attributes is required;
3. in one embodiment of the invention, a knowledge graph is a graph formed of nodes and edges that reflects the structure of knowledge, in the knowledge graph, nodes represent entities, edges represent relationships between the entities, and the first three-element information comprises two entities, a relationship between the two entities and attributes of a specific entity, so that the two entities, the relationship between the two entities and the attributes of the specific entity in the first three-element information can be mapped to each node and edge of the knowledge graph, in this process, the entity definitions, attribute definitions and relationship definitions in the first triplet information and the knowledge-graph must remain consistent, the knowledge graph to be constructed is generated based on the fact that the two entities contained in the first triple information, the relation between the two entities and the attribute of the specific entity can be mapped to the corresponding nodes and edges in the knowledge graph.
It should be noted that not all steps and modules in the above flows and system structure diagrams are necessary, and some steps or modules may be omitted according to actual needs. The execution order of the steps is not fixed and can be adjusted as required. The system structure described in the above embodiments may be a physical structure or a logical structure, that is, some modules may be implemented by the same physical entity, or some modules may be implemented by a plurality of physical entities, or some components in a plurality of independent devices may be implemented together.
In the above embodiments, the hardware unit may be implemented mechanically or electrically. For example, a hardware element may comprise permanently dedicated circuitry or logic (such as a dedicated processor, FPGA or ASIC) to perform the corresponding operations. The hardware elements may also comprise programmable logic or circuitry, such as a general purpose processor or other programmable processor, that may be temporarily configured by software to perform the corresponding operations. The specific implementation (mechanical, or dedicated permanent, or temporarily set) may be determined based on cost and time considerations.
While the invention has been shown and described in detail in the drawings and in the preferred embodiments, it is not intended to limit the invention to the embodiments disclosed, and it will be apparent to those skilled in the art that various combinations of the code auditing means in the various embodiments described above may be used to obtain further embodiments of the invention, which are also within the scope of the invention.
Claims (10)
1. The method for constructing the knowledge card is characterized by comprising the following steps:
acquiring at least one piece of original data from an original database;
determining at least one first triple information of the current original data aiming at each piece of original data in the at least one piece of original data, wherein each first triple information comprises two entities, a relation between the two entities or entity attribute information;
generating an ontology base of the knowledge graph to be constructed according to the first triple information;
generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed;
generating the knowledge card to be constructed according to the knowledge graph to be constructed;
when it is monitored that one piece of newly added original data exists in the original database, determining at least one newly added first triple information of the newly added original data;
updating the ontology base according to the at least one newly added first triple information;
updating the knowledge graph to be constructed according to the updated ontology base;
and updating the knowledge card to be constructed according to the updated knowledge graph to be constructed.
2. The method of claim 1,
the at least one piece of raw data includes: structured raw data, semi-structured raw data and unstructured raw data;
the determining, for each piece of raw data of the at least one piece of raw data, at least one first triplet information in the current raw data includes:
d1: determining whether the current original data is the structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured raw data as a first triplet of information;
d3: determining whether the current raw data is the semi-structured raw data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: taking the analyzed current original data as the first triple information;
d6: determining whether the current raw data is unstructured raw data;
d7: and when the current original data is determined to be the unstructured original data, extracting one first triple information in the current original data.
3. The method of claim 1,
the generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed comprises the following steps:
taking two entities contained in each first triple as two nodes of the knowledge graph to be constructed respectively, wherein the two entities have the same definition as the entities in the knowledge graph to be constructed;
taking the relationship or entity attribute information between the two entities contained in each first triple as an edge of the to-be-constructed knowledge graph, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the to-be-constructed knowledge graph;
and generating a knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
4. The method of claim 1,
the knowledge card to be constructed comprises: at least one card element;
the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph;
the generating the knowledge card to be constructed according to the knowledge graph to be constructed comprises the following steps:
determining a target template of the knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing the card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating the card to be constructed according to the target hyperlink and the target template.
5. The method of claim 1,
generating an ontology base of the knowledge graph to be constructed according to the first triple information, wherein the generating comprises:
constructing a mode layer of a knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, wherein the mode layer of the knowledge graph comprises at least one second triple information, each second triple information comprises two ontologies, a relation between the two ontologies or ontology attribute information, the two entities are instances corresponding to the two ontologies, and the data layer of the knowledge graph comprises the at least one first triple information;
and generating the ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
6. Knowledge card's construction equipment, its characterized in that includes:
the acquisition module is used for acquiring at least one piece of original data from an original database;
a determining module, configured to determine, for each piece of raw data in the at least one piece of raw data acquired by the acquiring module, at least one first triple information of the current raw data, where each first triple information includes two entities, a relationship between the two entities, or entity attribute information;
constructing a module: generating an ontology base of the knowledge graph to be constructed according to the first triple information determined by the determining module; generating the knowledge graph to be constructed according to the ontology base of the knowledge graph to be constructed; generating the knowledge card to be constructed according to the knowledge graph to be constructed;
an update module: the method comprises the steps of determining at least one newly added first triple information of newly added original data when it is monitored that one piece of newly added original data exists in the original database; updating the ontology base according to the at least one newly added first triple information; updating the knowledge graph to be constructed according to the updated ontology base; and updating the knowledge card to be constructed according to the updated knowledge graph to be constructed.
7. The apparatus of claim 6,
the at least one piece of raw data includes: structured raw data, semi-structured raw data and unstructured raw data;
the determining module is configured to perform:
d1: determining whether the current original data is the structured original data, if so, executing step D2, otherwise, executing step D3;
d2: determining the structured raw data as a first triplet of information;
d3: determining whether the current raw data is the semi-structured raw data, if so, executing step D4, otherwise, executing step D6;
d4: analyzing the current original data;
d5: taking the analyzed current original data as the first triple information;
d6: determining whether the current raw data is unstructured raw data;
d7: and when the current original data is determined to be the unstructured original data, extracting one first triple information in the current original data.
8. The apparatus of claim 6,
the construction module is configured to use two entities included in each of the first triples as two nodes of the to-be-constructed knowledge graph respectively, where the two entities are defined the same as entities in the to-be-constructed knowledge graph; taking the relationship or entity attribute information between the two entities contained in each first triple as an edge of the to-be-constructed knowledge graph, wherein the relationship or entity attribute definition between the two entities is the same as the relationship definition or entity attribute definition between the two entities in the to-be-constructed knowledge graph; and generating a knowledge graph to be constructed according to the two nodes and the edges constructed by each first triple.
9. The apparatus of claim 6,
the knowledge card to be constructed comprises: at least one card element;
the display mode of each card element comprises a line graph, a pie graph, a bubble graph, a radar graph and a relation graph;
the building module is further configured to perform:
determining a target template of the knowledge card to be constructed from a preset model library, wherein the model library is a basic template library of the overall interface display effect of the knowledge card to be constructed;
determining target card elements in the card to be constructed, wherein the target card elements are used for representing the card elements needing to be associated with the knowledge graph to be constructed;
adding a target hyperlink on the target card element, wherein the target hyperlink associates a first target entity contained in the target card element with a corresponding second target entity in the knowledge graph to be constructed, and when the target card element is triggered, the knowledge graph to be constructed jumps to the associated knowledge graph to be constructed;
and generating the card to be constructed according to the target hyperlink and the target template.
10. The apparatus of claim 6,
the building module is further configured to build a mode layer of a knowledge graph and a data layer of the knowledge graph according to at least one first triple information in each piece of original data, where the mode layer of the knowledge graph includes at least one second triple information, each second triple information includes two ontologies, a relationship between the two ontologies, or ontology attribute information, the two entities are instances corresponding to the two ontologies, and the data layer of the knowledge graph includes the at least one first triple information; and generating the ontology base of the knowledge graph to be constructed according to the mode layer of the knowledge graph and the data layer of the knowledge graph.
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Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115391545A (en) * | 2022-04-26 | 2022-11-25 | 航天宏图信息技术股份有限公司 | Knowledge graph construction method and device for multi-platform collaborative observation task |
Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107992514A (en) * | 2016-10-26 | 2018-05-04 | 谷歌有限责任公司 | The search and retrieval of structured message card |
| CN111444351A (en) * | 2020-03-24 | 2020-07-24 | 清华苏州环境创新研究院 | Method and device for constructing knowledge graph in industrial process field |
| CN111538847A (en) * | 2020-04-16 | 2020-08-14 | 北方民族大学 | Ningxia rice knowledge graph construction method |
| CN112328857A (en) * | 2020-10-30 | 2021-02-05 | 中国平安人寿保险股份有限公司 | Product knowledge aggregation method and device, computer equipment and storage medium |
| CN112328876A (en) * | 2020-11-03 | 2021-02-05 | 平安科技（深圳）有限公司 | Electronic card generation and pushing method and device based on knowledge graph |
-
2021
- 2021-02-07 CN CN202110167514.6A patent/CN112905612A/en active Pending
Patent Citations (5)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN107992514A (en) * | 2016-10-26 | 2018-05-04 | 谷歌有限责任公司 | The search and retrieval of structured message card |
| CN111444351A (en) * | 2020-03-24 | 2020-07-24 | 清华苏州环境创新研究院 | Method and device for constructing knowledge graph in industrial process field |
| CN111538847A (en) * | 2020-04-16 | 2020-08-14 | 北方民族大学 | Ningxia rice knowledge graph construction method |
| CN112328857A (en) * | 2020-10-30 | 2021-02-05 | 中国平安人寿保险股份有限公司 | Product knowledge aggregation method and device, computer equipment and storage medium |
| CN112328876A (en) * | 2020-11-03 | 2021-02-05 | 平安科技（深圳）有限公司 | Electronic card generation and pushing method and device based on knowledge graph |
Non-Patent Citations (1)
| Title |
|---|
| 徐增林 等: "知识图谱技术综述", 《电子科技大学学报》, vol. 45, no. 04, pages 589 - 606 * |
Cited By (1)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN115391545A (en) * | 2022-04-26 | 2022-11-25 | 航天宏图信息技术股份有限公司 | Knowledge graph construction method and device for multi-platform collaborative observation task |
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