CN108205564B - Knowledge system construction method and system - Google Patents
Knowledge system construction method and system Download PDFInfo
- Publication number
- CN108205564B CN108205564B CN201611179650.2A CN201611179650A CN108205564B CN 108205564 B CN108205564 B CN 108205564B CN 201611179650 A CN201611179650 A CN 201611179650A CN 108205564 B CN108205564 B CN 108205564B
- Authority
- CN
- China
- Prior art keywords
- subject
- knowledge
- words
- ontology
- word
- Prior art date
- Legal status (The legal status is an assumption and is not a legal conclusion. Google has not performed a legal analysis and makes no representation as to the accuracy of the status listed.)
- Expired - Fee Related
Links
- 238000010276 construction Methods 0.000 title claims abstract description 41
- 238000000034 method Methods 0.000 claims abstract description 34
- 230000008676 import Effects 0.000 claims description 6
- 238000011022 operating instruction Methods 0.000 claims description 2
- 238000012545 processing Methods 0.000 abstract description 19
- 230000008569 process Effects 0.000 abstract description 13
- 239000000284 extract Substances 0.000 abstract description 5
- 238000007726 management method Methods 0.000 description 39
- 230000006870 function Effects 0.000 description 18
- 238000010586 diagram Methods 0.000 description 14
- 238000005516 engineering process Methods 0.000 description 10
- 238000000605 extraction Methods 0.000 description 7
- 238000012552 review Methods 0.000 description 5
- 238000003860 storage Methods 0.000 description 4
- 239000002699 waste material Substances 0.000 description 4
- 238000004458 analytical method Methods 0.000 description 3
- 238000004891 communication Methods 0.000 description 3
- 230000008878 coupling Effects 0.000 description 3
- 238000010168 coupling process Methods 0.000 description 3
- 238000005859 coupling reaction Methods 0.000 description 3
- 238000012790 confirmation Methods 0.000 description 2
- 238000009826 distribution Methods 0.000 description 2
- 238000001914 filtration Methods 0.000 description 2
- 238000009472 formulation Methods 0.000 description 2
- 239000000203 mixture Substances 0.000 description 2
- 230000003287 optical effect Effects 0.000 description 2
- 230000000007 visual effect Effects 0.000 description 2
- 230000003044 adaptive effect Effects 0.000 description 1
- 238000012550 audit Methods 0.000 description 1
- 239000003086 colorant Substances 0.000 description 1
- 238000012217 deletion Methods 0.000 description 1
- 230000037430 deletion Effects 0.000 description 1
- 238000004519 manufacturing process Methods 0.000 description 1
- 238000013507 mapping Methods 0.000 description 1
- 238000012986 modification Methods 0.000 description 1
- 230000004048 modification Effects 0.000 description 1
- 238000006467 substitution reaction Methods 0.000 description 1
- 239000013589 supplement Substances 0.000 description 1
- 238000012549 training Methods 0.000 description 1
- 230000007704 transition Effects 0.000 description 1
- 238000012795 verification Methods 0.000 description 1
Images
Classifications
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- G06F—ELECTRIC DIGITAL DATA PROCESSING
- G06F16/00—Information retrieval; Database structures therefor; File system structures therefor
- G06F16/20—Information retrieval; Database structures therefor; File system structures therefor of structured data, e.g. relational data
- G06F16/22—Indexing; Data structures therefor; Storage structures
- G06F16/2282—Tablespace storage structures; Management thereof
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06F16/21—Design, administration or maintenance of databases
- G06F16/211—Schema design and management
-
- G—PHYSICS
- G06—COMPUTING; CALCULATING OR COUNTING
- 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
- G06F16/24—Querying
- G06F16/245—Query processing
- G06F16/2455—Query execution
- G06F16/24564—Applying rules; Deductive queries
Landscapes
- Engineering & Computer Science (AREA)
- Theoretical Computer Science (AREA)
- Databases & Information Systems (AREA)
- Data Mining & Analysis (AREA)
- Physics & Mathematics (AREA)
- General Engineering & Computer Science (AREA)
- General Physics & Mathematics (AREA)
- Software Systems (AREA)
- Computational Linguistics (AREA)
- Information Retrieval, Db Structures And Fs Structures Therefor (AREA)
Abstract
The embodiment of the invention provides a knowledge system construction method and a knowledge system construction system. The system comprises: the system comprises a keyword list management module, a field rule setting module, a subject word list management module, a field body management module and a user authority management module; the keyword table management module is used for acquiring keywords in the target field; the domain rule setting module is used for determining the setting rule and the body rule of the subject vocabulary; the subject word list management module is used for operating the subject words and the subject word list; the domain ontology management module is used for constructing an ontology; the user authority management module is used for verifying the operation authority of the user. The embodiment of the invention automatically extracts keywords in the document processing process through the knowledge system construction system, and fills a series of services such as the related relation and the attribute of the subject words and the knowledge elements based on the existing system, thereby achieving the purpose of quickly constructing the knowledge system, improving the utilization rate of document resources, improving the dynamic learning and updating capability of the knowledge system, and improving the intelligent automation degree.
Description
Technical Field
The embodiment of the invention relates to the field of digital publishing, in particular to a knowledge system construction method and a knowledge system construction system.
Background
Digital publishing is the digitalized inheritance of human culture, and is a new publishing industry which is established on the basis of high and new technologies such as computer technology, communication technology, network technology, streaming media technology, storage technology, display technology and the like, integrates and develops beyond the traditional publishing content. In the digital publishing process, all information is stored in a medium such as an optical disc, a magnetic disc and the like in a digital form of a uniform binary code, and the information is processed and received by a computer or a terminal device. It emphasizes the digitalization of content, production mode and operation flow, the digitalization of propagation carrier and the digitalization of reading consumption and learning form.
At present, a knowledge system in the field of digital publishing is constructed manually based on an industry subject vocabulary, a knowledge element set and the like, so that the construction time of the knowledge system is long, the utilization rate of literature resources is low, the dynamic learning and updating capability of the knowledge system is weak, and the intelligent automation degree is low.
Disclosure of Invention
The embodiment of the invention provides a knowledge system construction method and a knowledge system construction system, which aim to solve the problems of low speed of knowledge system construction, low utilization rate of literature resources, weak dynamic learning and updating capability of the system and low intelligent automation degree.
One aspect of an embodiment of the present invention is to provide a knowledge system construction system, including:
the keyword table management module is used for acquiring keywords in a target field, and editing, deleting and releasing the keywords;
the domain rule setting module is used for determining the setting rule and the body rule of the subject vocabulary;
the subject word list management module is used for determining a subject word according to the keyword; establishing a subject word list according to the subject words and the setting rules of the subject word list; newly adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing the subject term; newly creating, editing and deleting the theme word list;
the domain ontology management module is used for acquiring the knowledge elements of the target domain; establishing an ontology according to the knowledge association between the model of the knowledge elements and different knowledge elements; importing, exporting, editing and deleting the body; adding, editing, deleting, inquiring, visually displaying and associating resources to the knowledge element;
and the user authority management module is used for acquiring the user information and verifying the operation authority of the user according to the user information.
Another aspect of the embodiments of the present invention is to provide a knowledge system construction method, including:
acquiring keywords in a target field, and determining a subject term according to the keywords;
establishing a subject word list according to the subject words and the setting rules of the subject word list;
operating the subject term according to a first operation instruction, wherein the operation on the subject term comprises the following steps: adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing;
operating the theme word list according to a second operation instruction, wherein the operating on the theme word list comprises the following steps: newly creating, editing and deleting;
acquiring a knowledge element of the target field;
establishing an ontology according to the knowledge association between the model of the knowledge elements and different knowledge elements;
operating the body according to a third operating instruction, wherein the operating of the body comprises: importing, exporting, editing and deleting;
operating the knowledge element according to a fourth operation instruction, wherein the operating on the knowledge element comprises the following steps: adding, editing, deleting, inquiring, visually displaying and associating resources;
and acquiring user information, and verifying the operation authority of the user according to the user information.
According to the knowledge system construction method and system provided by the embodiment of the invention, a series of services such as automatic extraction of key words in the document processing process through the knowledge system construction system, filling of related relations and attributes of subject words and knowledge elements based on the existing system and the like are performed, so that the purpose of quickly constructing the knowledge system is achieved, the document resource utilization rate is improved, the dynamic learning and updating capability of the knowledge system is improved, and the intelligent automation degree is improved.
Drawings
FIG. 1 is a block diagram of a knowledge hierarchy building system provided by an embodiment of the present invention;
FIG. 2 is a functional diagram of a keyword table management module according to an embodiment of the present invention;
FIG. 3 is a functional diagram of a domain rule setting module according to an embodiment of the present invention;
FIG. 4 is a functional diagram of a subject vocabulary management module according to an embodiment of the present invention;
fig. 5 is a functional diagram of a domain ontology management module according to an embodiment of the present invention;
FIG. 6 is a task flow diagram provided by an embodiment of the invention;
FIG. 7 is a task flow diagram provided by another embodiment of the present invention;
FIG. 8 is a flowchart of a knowledge system construction method provided by an embodiment of the invention.
Detailed Description
FIG. 1 is a block diagram of a knowledge hierarchy building system provided by an embodiment of the present invention. As shown in fig. 1, the knowledge system construction system provided by this embodiment includes: the system comprises a keyword list management module, a field rule setting module, a subject word list management module, a field body management module and a user authority management module.
And the keyword table management module is used for managing the management operations of newly adding, editing, deleting, importing, exporting, discovering and releasing the new words as the subject words of the keywords in the system, specifically acquiring the keywords in the target field, and editing, deleting and releasing the keywords.
And the field rule setting module is used for managing the content standard setting of all word lists and bodies in the field, and specifically determining the theme word list setting rule and the body rule.
The theme word list management module is used for managing the list of the theme word list and the theme words in the list, and particularly determining the theme words according to the keywords; establishing a subject word list according to the subject words and the setting rules of the subject word list; newly adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing the subject term; and newly creating, editing and deleting the theme word list.
The domain ontology management module is used for managing a domain ontology, a knowledge element model and a knowledge element, and specifically acquiring the knowledge element of the target domain; establishing an ontology according to the knowledge association between the model of the knowledge elements and different knowledge elements; importing, exporting, editing and deleting the body; and adding, editing, deleting, inquiring, visually displaying and associating resources to the knowledge element.
And the user authority management module is used for managing the user and the system authority set for the user, specifically, acquiring user information and verifying the operation authority of the user according to the user information.
According to the embodiment, a knowledge system construction system automatically extracts keywords in the document processing process, and a series of services such as the related relation and attributes of subject words and knowledge elements are filled based on the existing system, so that the purpose of quickly constructing a knowledge system is achieved, the document resource utilization rate is improved, the dynamic learning and updating capability of the knowledge system is improved, and the intelligent automation degree is improved.
Fig. 2 is a functional schematic diagram of a keyword table management module according to an embodiment of the present invention. As shown in fig. 2, on the basis of the above embodiment, the keyword table management module is specifically configured to at least one of the following: taking the newly added subject word in the subject word list as the key word; acquiring keywords in the target field input by a user; taking words in a preset word list as the keywords; extracting words in the text data uploaded by the user, and taking the words in the text data as the keywords.
The key words are one of the sources of the subject words, and the management of the key word list is the basis of the construction of knowledge management. The module provides functions of adding, editing, deleting, importing, exporting, discovering new words and publishing the new words as subject words.
As shown in fig. 2, in the keyword table construction, there are four ways for the system to obtain keywords: subject word write back, manually adding keywords, keyword import, and new word discovery.
And the subject word write-back function is that after a new subject word is added in the subject word list, the system automatically writes back the new subject word to the keyword list as a new keyword.
Manually adding keywords: the function can meet the requirement of manually inputting the keywords by the user and realize flexible supplement of the keyword list.
Importing keywords: the function can meet the requirement of a user for building a knowledge system based on the existing industry word list, and can directly import the existing word list into the system to quickly build a basic word list of the knowledge system.
Discovery of new words: the function can extract new words in the text according to the text data uploaded by the user, and the new words are updated to the keyword list after being confirmed by the user. The function can build a keyword list based on the existing linguistic data, and promotes the construction of the keyword list while improving the utilization rate of the linguistic data documents.
Keyword editing/deleting: for the existing keyword list, a user can manually edit and delete certain keywords, and the accurate control on the keyword list is realized.
Keyword release: for the confirmed correct keywords, the keywords can be released as the subject words in the subject word list of a certain field in an upgrading way.
Fig. 3 is a functional schematic diagram of a domain rule setting module according to an embodiment of the present invention. As shown in fig. 3, on the basis of the above embodiment, the theme vocabulary setting rule includes: the feature word definition rules of the subject words, the attribute definition rules of the subject words and the relationship definition rules among the subject words.
The domain rule setting module comprises the functions of domain creation and editing, theme vocabulary rule setting and body rule setting. The domain rule setting module sets the content specifications of all word lists and bodies in the domain, and the subject word list and the body in the domain inherit the rules of the domain.
The method comprises the following steps of setting up the rules of the subject word list under the field, wherein the rules comprise the management of feature word definition of the subject words in the field, attribute definition of the subject words and definition of the relationships among words. The feature word management of the subject word can be used for managing the feature words and feature classifications which can be selected by the subject word in the field and are adaptive to the subject word, and when the subject word is checked and screened, the rapid positioning can be realized through the feature classifications and the feature words of the subject word; the attribute management of the subject term can manage the attribute categories required to be filled in when the subject term in the field is edited, such as pinyin attribute, annotation attribute and the like; by managing the relationship between words, the relationship between words of subject words in the field can be determined, wherein the relationship between words comprises two dimensions of generation, attribute score, reference or superior word, inferior word, synonym and related word.
The domain ontology rules comprise abstract knowledge meta-model definitions and knowledge meta-relation definitions. The abstract knowledge meta-model definition includes assignments to model attributes, definitions of model instance attributes, and definitions of model instance styles. The model attribute comprises a model name and a parent model inherited by the model name; the definition of the model instance attribute comprises the definition of the attribute name, the input form and the verification mode of the model instance (namely the knowledge element); the definition of the model style defines the color style of the model instance in the knowledge element map. The knowledge meta-relation defines the possible association relation among the knowledge meta-model instances. The content of the relationship definition includes: relationship names, relationship types, relationship colors, relationship descriptions, and mapping relationships between the relationships and the knowledge meta-model attributes.
Fig. 4 is a functional diagram of a subject vocabulary management module according to an embodiment of the present invention. As shown in fig. 4, in addition to the above embodiment, the subject term is a term having certain characteristics in a certain field including attributes, classifications, associated subject terms and associated resources. The invention supports the requirements of combing related knowledge for publishing enterprises to construct a subject vocabulary and providing knowledge service for readers.
The subject vocabulary construction comprises two parts of vocabulary rule formulation and content editing and adding, the vocabulary rule formulation is completed in a field rule setting module, and a subject vocabulary management module provides a function of editing and adding the content of the subject vocabulary. The main stroke word list management module comprises list management of the subject word list and management of subject words in the list.
The table management of the subject word table comprises the functions of creating, editing and deleting the subject word table of the field, and the field and the word table name of the subject word table can be selected when the subject word table is created and edited.
The management of the subject term in the table comprises the functions of adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing the subject term.
The acquisition sources of the subject term in the vocabulary include four types:
1) based on the traditional subject term construction method, the manual word discrimination and vocabulary compilation work is realized by adopting a mode of manually adding field experts;
2) the method is derived from published keywords, and the establishment of subject words in a word list is realized;
3) constructing a subject word list by adopting an external import mode based on the existing subject words;
4) the method is derived from the existing knowledge elements in the knowledge system to write back, and forms subject words in the vocabulary.
By the four forms of subject term obtaining modes, the flexible and quick construction of the word list is realized, and the problems of low processing speed, incomplete coverage and document resource waste caused by single mode linear processing are avoided. Meanwhile, in the construction process of the four forms, the subject term is edited, the related subject term is filled and the related resources are connected in a service mode combining manual work and automatic extraction and analysis, and the word list construction speed is improved.
The editing content of the subject term comprises: the method comprises the following steps of providing a theme word name, a theme word attribute, a theme word characteristic, an affiliated classification and a related word of the theme word. The subject term attributes comprise pinyin, vocabulary entry paraphrases, free words and the like of the subject term, and can be set in the domain rule setting module. The related words of the subject words can be specified in a fuzzy query mode, a rapid positioning and filtering mode of the classification and the characteristics of the subject words, and the setting of the inter-word relation is managed in a domain rule setting module.
The service combining the manual extraction and the automatic extraction analysis comprises the following steps:
related word filling: according to the word-building characteristics, the characteristics and the attributes of the subject words, related words of the subject words can be intelligently supplemented, and the related words can be filled after being manually confirmed and audited.
And (3) linking associated resources: according to the subject word name, the free word and the like, the related resources can be automatically connected and confirmed by manual examination.
The topic word list acquires the topic words through the analysis mode, the word list is constructed, the topic words are edited through a mode of combining manual work and intelligent service, the attribute of the topic words is filled, and associated resources are connected, so that the topic word list construction of a knowledge system is realized. For the subject words in the word list, the invention provides the visual display function of the subject words and related words, and can visually check the attributes and associated resources of the subject words and the subject word map with a certain inter-word relationship.
Fig. 5 is a functional diagram of a domain ontology management module according to an embodiment of the present invention. As shown in fig. 5, on the basis of the above embodiment, the domain ontology management module is specifically configured to at least one of the following: receiving a newly added knowledge element input by a user; acquiring a knowledge element of the target field according to the issued subject term; determining the knowledge elements of the target field according to an abstract knowledge element model, the knowledge elements and the corpora; and obtaining an ontology knowledge element by constructing an ontology according to the OWL ontology importing mode and the offline ontology. After the domain ontology management module obtains the ontology knowledge element, the domain ontology management module is further configured to: setting the incidence relation of the knowledge elements and hooking the related resources of the knowledge elements.
The domain ontology is a network system formed by numerous knowledge elements and knowledge associations among the knowledge elements, formalization capability and high knowledge reasoning capability can be further enhanced by constructing the domain ontology, and more relationships among concepts can be obtained through complex logical reasoning.
The domain ontology management module provides management of domain ontologies and management of knowledge elements in the domain.
And managing the domain ontology, including importing, exporting, editing and modifying the ontology.
The ontology importing function can facilitate basic users to quickly construct an ontology based on existing OWL files. OWL is an ontology description language, can describe the complete domain ontology, use the domain ontology's of OWL language description offline file, can realize the leading-in of the system; after the OWL file is imported, the method and the system provided by the invention analyze the OWL file, obtain the knowledge association and the knowledge meta information of the ontology, and store the knowledge association and the knowledge meta information in the database.
The ontology export function can export a standard knowledge system into an OWL file for editing by using an ontology construction tool offline.
The management of the knowledge elements in the field comprises the functions of adding, editing, deleting, inquiring, visually displaying and associating resources to the knowledge elements. Wherein the attribute of the knowledge element can be set in a domain rule setting module.
The source mode of the knowledge element in the ontology comprises four types:
1) a mode of adding new knowledge elements manually by domain experts;
2) from published subject matter;
3) the knowledge elements are automatically extracted based on a large amount of training of abstract knowledge element models, knowledge elements and corpora;
4) by means of an OWL ontology importing mode, an ontology can be quickly constructed on the basis of an existing offline ontology, and ontology knowledge elements are obtained.
After the ontology knowledge elements are acquired in the above manner, the setting of the association relationship of the knowledge elements and the hooking of related resources are further completed.
The setting of the incidence relation of the knowledge elements is based on the definition of the knowledge element model relation in the domain rule setting module, and the positioning and filtering are carried out in the modes of fuzzy inquiry, pinyin index, knowledge element source, the located process and the like, and then the information is determined by manual selection.
There are two methods for hooking knowledge element related resources: (1) intelligently recommending related resources or retrieving and acquiring related resources in a mode of combining manual work and intelligent recommendation according to information such as names, keywords and authors of the resources needing to be hooked, and hooking after confirmation; (2) and intelligently recommending and hooking resources according to the name, the attribute and the like of the knowledge element.
After the acquisition, the editing, the setting of the incidence relation and the hanging of the related resources of the knowledge elements are completed, the map of the body formed by the knowledge elements can be visually checked through the visual display function, and the details of the small map formed by the attributes of the knowledge elements, the related resources and the related knowledge elements can be visually checked.
FIG. 6 is a task flow diagram provided by an embodiment of the invention; fig. 7 is a task flow diagram provided by another embodiment of the present invention. As shown in fig. 6, on the basis of the above embodiment, the user and authority management module is used for managing users, user roles, and user browsing and operating authorities.
The user roles in the invention are divided into three categories: industry experts, publishers, and system administrators. The industry experts are responsible for editing and managing the knowledge system, including editing operation and examination of the subject word list and the domain ontology knowledge content; the user of the publishing company is responsible for auditing and confirming the operation performed by the expert; and the system administrator is responsible for managing user and role authorities and setting field rules.
The user operation permission comprises permission of editing and filling word lists and body contents of a user, such as creating, editing, importing, exporting and the like of the keyword list, the subject word list and the field body.
As shown in fig. 6, the task types in the present invention include two types: and processing a task and auditing the task, wherein the task object is a subject word list and a field ontology. The states of the subject words and the knowledge elements in the ontology are uniformly divided into to-be-indexed, to-be-audited and to-be-warehoused, and the state transition is driven by a task.
The quantifiable tasks in the system share four categories of theme word processing, theme word review, knowledge element processing and knowledge element review. The theme word processing is to perform attribute filling, feature selection and inter-word relationship establishment on the theme words to be indexed; the subject term review is to confirm again the processing result of the term in the state to be reviewed; the knowledge element processing is to perform attribute filling, accessory uploading and relation establishment on the knowledge element in a to-be-indexed state; and the element audit is to confirm the processing result of the element under the state to be audited again.
In a task, any kind of task comprises three steps of creation and distribution of the task, processing and submission of the task, and auditing and confirmation of a task result. The task flow is shown in figure 7 below.
The method and the system for constructing the knowledge system in the digital publishing field are adopted, so that the knowledge system in the digital publishing field can be quickly and flexibly constructed on the basis of document resources and word lists by means of combining an intelligent technology with a manual review mode. By quickly importing the existing resources and matching with an intelligent extraction technology and a manual processing and auditing process, the quick construction of a knowledge system can be realized, the utilization rate of document resources is improved, and the waste of personnel and resources caused by linear workflow is avoided.
FIG. 8 is a flowchart of a knowledge system construction method provided by an embodiment of the invention. As shown in fig. 8, the method comprises the following specific steps:
step S101, keywords in the target field are obtained, and the subject term is determined according to the keywords.
And S102, establishing a subject word list according to the subject words and the setting rules of the subject word list.
Step S103, operating the subject term according to a first operation instruction, wherein the operation on the subject term comprises the following steps: adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing.
Step S104, operating the theme word list according to a second operation instruction, wherein the operating on the theme word list comprises the following steps: new creation, editing and deletion.
And S105, acquiring the knowledge element of the target field.
And S106, constructing an ontology according to the knowledge association between the model of the knowledge element and different knowledge elements.
Step S107, operating the body according to a third operation instruction, wherein the operation on the body comprises the following steps: import, export, edit, delete.
Step S108, operating the knowledge element according to a fourth operation instruction, wherein the operating on the knowledge element comprises: adding, editing, deleting, inquiring, visually displaying and associating resources.
Step S109, obtaining user information, and verifying the operation authority of the user according to the user information.
The method principle described in step S101 to step S109 is consistent with the knowledge system building system principle described in the above embodiment, and is not described here again.
According to the embodiment, a knowledge system construction system automatically extracts keywords in the document processing process, and a series of services such as the related relation and attributes of subject words and knowledge elements are filled based on the existing system, so that the purpose of quickly constructing a knowledge system is achieved, the document resource utilization rate is improved, the dynamic learning and updating capability of the knowledge system is improved, and the intelligent automation degree is improved.
On the basis of the above embodiment, the obtaining of the keywords in the target field includes at least one of the following: taking the newly added subject word in the subject word list as the key word; acquiring keywords in the target field input by a user; taking words in a preset word list as the keywords; extracting words in the text data uploaded by the user, and taking the words in the text data as the keywords.
The theme vocabulary setting rule comprises the following steps: the feature word definition rules of the subject words, the attribute definition rules of the subject words and the relationship definition rules among the subject words.
The acquiring of the knowledge element of the target field includes at least one of the following: receiving a newly added knowledge element input by a user; acquiring a knowledge element of the target field according to the issued subject term; determining the knowledge elements of the target field according to an abstract knowledge element model, the knowledge elements and the corpora; and obtaining an ontology knowledge element by constructing an ontology according to the OWL ontology importing mode and the offline ontology.
In addition, after obtaining the ontology knowledge element, the method further includes: setting the incidence relation of the knowledge elements and hooking the related resources of the knowledge elements.
The knowledge system construction method provided by the embodiment of the invention can be specifically realized by the knowledge system construction system provided by fig. 1, and specific functions are not described herein again.
The method and the system for constructing the knowledge system in the digital publishing field are adopted, so that the knowledge system in the digital publishing field can be quickly and flexibly constructed on the basis of document resources and word lists by means of combining an intelligent technology with a manual review mode. By quickly importing the existing resources and matching with an intelligent extraction technology and a manual processing and auditing process, the quick construction of a knowledge system can be realized, the utilization rate of document resources is improved, and the waste of personnel and resources caused by linear workflow is avoided.
In summary, the embodiment of the invention automatically extracts keywords in the document processing process through the knowledge system construction system, and fills a series of services such as the correlation and attributes of the subject words and the knowledge elements based on the existing system, so as to achieve the purpose of quickly constructing the knowledge system, improve the utilization rate of document resources, improve the dynamic learning and updating capability of the knowledge system, and improve the intelligent automation degree; by adopting the method and the system for constructing the knowledge system in the digital publishing field, the knowledge system in the digital publishing field can be quickly and flexibly constructed by taking document resources and word lists as the basis and combining an intelligent technology with a manual auditing mode as a means. By quickly importing the existing resources and matching with an intelligent extraction technology and a manual processing and auditing process, the quick construction of a knowledge system can be realized, the utilization rate of document resources is improved, and the waste of personnel and resources caused by linear workflow is avoided.
In the embodiments provided in the present invention, it should be understood that the disclosed apparatus and method may be implemented in other ways. For example, the above-described apparatus embodiments are merely illustrative, and for example, the division of the units is only one logical division, and other divisions may be realized in practice, for example, a plurality of units or components may be combined or integrated into another system, or some features may be omitted, or not executed. In addition, the shown or discussed mutual coupling or direct coupling or communication connection may be an indirect coupling or communication connection through some interfaces, devices or units, and may be in an electrical, mechanical or other form.
The units described as separate parts may or may not be physically separate, and parts displayed as units may or may not be physical units, may be located in one place, or may be distributed on a plurality of network units. Some or all of the units can be selected according to actual needs to achieve the purpose of the solution of the embodiment.
In addition, functional units in the embodiments of the present invention may be integrated into one processing unit, or each unit may exist alone physically, or two or more units are integrated into one unit. The integrated unit can be realized in a form of hardware, or in a form of hardware plus a software functional unit.
The integrated unit implemented in the form of a software functional unit may be stored in a computer readable storage medium. The software functional unit is stored in a storage medium and includes several instructions to enable a computer device (which may be a personal computer, a server, or a network device) or a processor (processor) to execute some steps of the methods according to the embodiments of the present invention. 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.
It is obvious to those skilled in the art that, for convenience and simplicity of description, the foregoing division of the functional modules is merely used as an example, and in practical applications, the above function distribution may be performed by different functional modules according to needs, that is, the internal structure of the device is divided into different functional modules to perform all or part of the above described functions. For the specific working process of the device described above, reference may be made to the corresponding process in the foregoing method embodiment, which is not described herein again.
Finally, it should be noted that: the above embodiments are only used to illustrate the technical solution of the present invention, and not to limit the same; while the invention has been described in detail and with reference to the foregoing embodiments, it will be understood by those skilled in the art that: the technical solutions described in the foregoing embodiments may still be modified, or some or all of the technical features may be equivalently replaced; and the modifications or the substitutions do not make the essence of the corresponding technical solutions depart from the scope of the technical solutions of the embodiments of the present invention.
Claims (10)
1. A knowledge hierarchy building system, comprising:
the keyword table management module is used for acquiring keywords in a target field, and editing, deleting and releasing the keywords;
the domain rule setting module is used for determining a theme vocabulary setting rule and an ontology rule;
the subject word list management module is used for determining a subject word according to the keyword; establishing a subject word list according to the subject words and the setting rules of the subject word list; newly adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing the subject term; newly creating, editing and deleting the theme word list;
the domain ontology management module is used for acquiring the knowledge elements of the target domain; establishing an ontology according to the knowledge association between the model of the knowledge elements and different knowledge elements; importing, exporting, editing and deleting the body; adding, editing, deleting, inquiring, visually displaying and associating resources to the knowledge element;
the user authority management module is used for acquiring user information and verifying the operation authority of a user according to the user information;
the establishing a subject vocabulary according to the subject word and the setting rule of the subject vocabulary comprises the following steps:
based on the traditional method for constructing the subject term, manual word discrimination and the compiling work of the subject term list are realized by adopting a mode of manually adding field experts;
based on the issued keywords, the construction of the subject term in the word list is realized;
constructing the subject word list by adopting an external import mode based on the existing subject words;
and writing back the knowledge elements based on the existing knowledge system to form the subject words in the word list.
2. The knowledge system building system of claim 1, wherein the keyword table management module is specifically configured to at least one of:
taking the newly added subject word in the subject word list as the key word;
acquiring keywords in the target field input by a user;
taking words in a preset word list as the keywords;
extracting words in the text data uploaded by the user, and taking the words in the text data as the keywords.
3. The system of knowledge architecture construction of claim 1, wherein the subject vocabulary setting rules comprise: the feature word definition rules of the subject words, the attribute definition rules of the subject words and the relationship definition rules among the subject words.
4. The knowledge system building system of claim 1, wherein the domain ontology management module is specifically configured to at least one of:
receiving a newly added knowledge element input by a user;
acquiring a knowledge element of the target field according to the issued subject term;
determining the knowledge elements of the target field according to an abstract knowledge element model, the knowledge elements and the corpora;
and obtaining an ontology knowledge element by constructing an ontology according to the OWL ontology importing mode and the offline ontology.
5. The system of knowledge architecture construction of claim 4, wherein after obtaining the ontology knowledgebase, the domain ontology management module is further configured to:
setting the incidence relation of the knowledge elements and hooking the related resources of the knowledge elements.
6. A knowledge system construction method is characterized by comprising the following steps:
acquiring keywords in a target field, and determining a subject term according to the keywords;
establishing a subject word list according to the subject words and the setting rules of the subject word list;
operating the subject term according to a first operation instruction, wherein the operation on the subject term comprises the following steps: adding, editing, deleting, inquiring, visually displaying, exporting, associating resources and releasing;
operating the theme word list according to a second operation instruction, wherein the operating on the theme word list comprises the following steps: newly creating, editing and deleting;
acquiring a knowledge element of the target field;
establishing an ontology according to the knowledge association between the model of the knowledge elements and different knowledge elements;
operating the body according to a third operating instruction, wherein the operating of the body comprises: importing, exporting, editing and deleting;
operating the knowledge element according to a fourth operation instruction, wherein the operating on the knowledge element comprises the following steps: adding, editing, deleting, inquiring, visually displaying and associating resources;
acquiring user information, and verifying the operation authority of a user according to the user information;
the establishing a subject vocabulary according to the subject word and the setting rule of the subject vocabulary comprises the following steps:
based on the traditional method for constructing the subject term, manual word discrimination and the compiling work of the subject term list are realized by adopting a mode of manually adding field experts;
based on the issued keywords, the construction of the subject term in the word list is realized;
constructing the subject word list by adopting an external import mode based on the existing subject words;
and writing back the knowledge elements based on the existing knowledge system to form the subject words in the word list.
7. The method of claim 6, wherein the obtaining keywords in the target domain comprises at least one of:
taking the newly added subject word in the subject word list as the key word;
acquiring keywords in the target field input by a user;
taking words in a preset word list as the keywords;
extracting words in the text data uploaded by the user, and taking the words in the text data as the keywords.
8. The method of claim 6, wherein the subject vocabulary setting rules comprise: the feature word definition rules of the subject words, the attribute definition rules of the subject words and the relationship definition rules among the subject words.
9. The method of claim 6, wherein the obtaining the knowledge element of the target domain comprises at least one of:
receiving a newly added knowledge element input by a user;
acquiring a knowledge element of the target field according to the issued subject term;
determining the knowledge elements of the target field according to an abstract knowledge element model, the knowledge elements and the corpora;
and obtaining an ontology knowledge element by constructing an ontology according to the OWL ontology importing mode and the offline ontology.
10. The method of claim 9, wherein after obtaining the ontology knowledge element, further comprising:
setting the incidence relation of the knowledge elements and hooking the related resources of the knowledge elements.
Priority Applications (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611179650.2A CN108205564B (en) | 2016-12-19 | 2016-12-19 | Knowledge system construction method and system |
Applications Claiming Priority (1)
| Application Number | Priority Date | Filing Date | Title |
|---|---|---|---|
| CN201611179650.2A CN108205564B (en) | 2016-12-19 | 2016-12-19 | Knowledge system construction method and system |
Publications (2)
| Publication Number | Publication Date |
|---|---|
| CN108205564A CN108205564A (en) | 2018-06-26 |
| CN108205564B true CN108205564B (en) | 2021-04-09 |
Family
ID=62601944
Family Applications (1)
| Application Number | Title | Priority Date | Filing Date |
|---|---|---|---|
| CN201611179650.2A Expired - Fee Related CN108205564B (en) | 2016-12-19 | 2016-12-19 | Knowledge system construction method and system |
Country Status (1)
| Country | Link |
|---|---|
| CN (1) | CN108205564B (en) |
Families Citing this family (2)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN109545285A (en) * | 2018-11-13 | 2019-03-29 | 中国核动力研究设计院 | A kind of knowledge application method of nuclear reactor digital experiment platform |
| CN111061828B (en) * | 2019-11-29 | 2023-08-29 | 华中师范大学 | Digital library knowledge retrieval method and device |
Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102207945A (en) * | 2010-05-11 | 2011-10-05 | 天津海量信息技术有限公司 | Knowledge network-based text indexing system and method |
| CN102567464A (en) * | 2011-11-29 | 2012-07-11 | 西安交通大学 | Theme map expansion based knowledge resource organizing method |
| CN103729402A (en) * | 2013-11-22 | 2014-04-16 | 浙江大学 | Method for establishing mapping knowledge domain based on book catalogue |
| CN103744846A (en) * | 2013-08-13 | 2014-04-23 | 北京航空航天大学 | Multidimensional dynamic local knowledge map and constructing method thereof |
| CN103745288A (en) * | 2013-08-13 | 2014-04-23 | 北京航空航天大学 | Knowledge-based cooperative method of complex product development process |
| CN105786980A (en) * | 2016-02-14 | 2016-07-20 | 广州神马移动信息科技有限公司 | Method and apparatus for combining different examples for describing same entity and equipment |
-
2016
- 2016-12-19 CN CN201611179650.2A patent/CN108205564B/en not_active Expired - Fee Related
Patent Citations (6)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102207945A (en) * | 2010-05-11 | 2011-10-05 | 天津海量信息技术有限公司 | Knowledge network-based text indexing system and method |
| CN102567464A (en) * | 2011-11-29 | 2012-07-11 | 西安交通大学 | Theme map expansion based knowledge resource organizing method |
| CN103744846A (en) * | 2013-08-13 | 2014-04-23 | 北京航空航天大学 | Multidimensional dynamic local knowledge map and constructing method thereof |
| CN103745288A (en) * | 2013-08-13 | 2014-04-23 | 北京航空航天大学 | Knowledge-based cooperative method of complex product development process |
| CN103729402A (en) * | 2013-11-22 | 2014-04-16 | 浙江大学 | Method for establishing mapping knowledge domain based on book catalogue |
| CN105786980A (en) * | 2016-02-14 | 2016-07-20 | 广州神马移动信息科技有限公司 | Method and apparatus for combining different examples for describing same entity and equipment |
Also Published As
| Publication number | Publication date |
|---|---|
| CN108205564A (en) | 2018-06-26 |
Similar Documents
| Publication | Publication Date | Title |
|---|---|---|
| US10733193B2 (en) | Similar document identification using artificial intelligence | |
| US11086896B2 (en) | Dynamic composite data dictionary to facilitate data operations via computerized tools configured to access collaborative datasets in a networked computing platform | |
| Burgueño et al. | An NLP-based architecture for the autocompletion of partial domain models | |
| US20190121807A1 (en) | Computerized tools to develop and manage data-driven projects collaboratively via a networked computing platform and collaborative datasets | |
| US20190066052A1 (en) | Computerized tools to facilitate data project development via data access layering logic in a networked computing platform including collaborative datasets | |
| CN104298478B (en) | The deduction acted based on filename to thesaurus | |
| Sjöberg et al. | Digital me: Controlling and making sense of my digital footprint | |
| US20220019905A1 (en) | Enterprise knowledge graph building with mined topics and relationships | |
| CN106663101A (en) | Ontology mapping method and apparatus | |
| EP3270303A1 (en) | An automated monitoring and archiving system and method | |
| CN111145051A (en) | Method and device for generating arbitration electronic document | |
| WO2022019973A1 (en) | Enterprise knowledge graphs using enterprise named entity recognition | |
| CN109800354B (en) | Resume modification intention identification method and system based on block chain storage | |
| Leone et al. | Taking stock of legal ontologies: a feature-based comparative analysis | |
| AU2015331030A1 (en) | System generator module for electronic document and electronic file | |
| KR20180059602A (en) | Method and system for sharing user-defined Enterprise Resource Planning function and computing system performing the same | |
| CN110795923A (en) | Automatic generation system and generation method of technical document based on natural language processing | |
| Miksa et al. | Framing the scope of the common data model for machine-actionable data management plans | |
| CN108205564B (en) | Knowledge system construction method and system | |
| Yang et al. | User story clustering in agile development: a framework and an empirical study | |
| CN117236624A (en) | Issue repairer recommendation method and apparatus based on dynamic graph | |
| CN114564938A (en) | Document parsing method and device, storage medium and processor | |
| CN116595191A (en) | Construction method and device of interactive low-code knowledge graph | |
| CN115543428A (en) | Simulated data generation method and device based on strategy template | |
| Zemmouchi-Ghomari et al. | Ontology versus terminology, from the perspective of ontologists |
Legal Events
| Date | Code | Title | Description |
|---|---|---|---|
| PB01 | Publication | ||
| PB01 | Publication | ||
| SE01 | Entry into force of request for substantive examination | ||
| SE01 | Entry into force of request for substantive examination | ||
| GR01 | Patent grant | ||
| GR01 | Patent grant | ||
| TR01 | Transfer of patent right | ||
| TR01 | Transfer of patent right |
Effective date of registration: 20230609 Address after: 3007, Hengqin international financial center building, No. 58, Huajin street, Hengqin new area, Zhuhai, Guangdong 519031 Patentee after: New founder holdings development Co.,Ltd. Patentee after: BEIJING FOUNDER ELECTRONICS Co.,Ltd. Address before: 100871, Beijing, Haidian District, Cheng Fu Road, No. 298, Zhongguancun Fangzheng building, 9 floor Patentee before: PEKING UNIVERSITY FOUNDER GROUP Co.,Ltd. Patentee before: BEIJING FOUNDER ELECTRONICS Co.,Ltd. |
|
| CF01 | Termination of patent right due to non-payment of annual fee | ||
| CF01 | Termination of patent right due to non-payment of annual fee |
Granted publication date: 20210409 |