CN108536872B - Method and device for optimizing knowledge base structure - Google Patents
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Abstract
The invention discloses a method and a device for optimizing a knowledge base structure, wherein the method comprises the following steps: establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge records corresponding to each knowledge node, determining whether a target knowledge record meeting preset conditions exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base, and associating the target knowledge record with the new knowledge node if the target knowledge record exists. Compared with the prior art, the embodiment of the invention does not need to add a new knowledge record to each new knowledge node, but can associate the existing knowledge records of other knowledge nodes to the new knowledge node to complete the updating of the knowledge base, thereby simplifying the updating process of the knowledge base and effectively reducing the updating cost.
Description
Technical Field
The invention relates to the field of knowledge bases, in particular to a method and a device for optimizing a knowledge base structure.
Background
In the education industry, knowledge bases (question bases) are always the key points and hot points of attention. The common knowledge base adopts a structure which is often a tree or a list, wherein the knowledge base with the tree structure is formed by summarizing knowledge points into a tree hierarchy and then establishing the knowledge base according to the tree structure; the knowledge base with the list structure is formed by dividing the knowledge points into a plurality of chapters and establishing the knowledge base according to the sequence of the chapters.
Although the two conventional knowledge base structures classify specific knowledge points clearly and are convenient to search, the restriction on establishing a huge knowledge system is large, when the content in the knowledge base needs to be updated, the knowledge base needs to be changed greatly, the updating cost of the knowledge base is high, and the knowledge base is not beneficial to being enriched and perfected continuously in the using process.
Disclosure of Invention
The embodiment of the invention provides a method and a device for optimizing a knowledge base structure, which can solve the technical problems of complex updating process and higher updating cost of the knowledge base structure in the prior art.
To achieve the above object, a first aspect of the present invention provides a method for optimizing a knowledge base structure, the method comprising:
establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
when a new knowledge node is recorded in the knowledge base, determining whether a target knowledge record meeting a preset condition exists in the knowledge records of each knowledge node;
and if the target knowledge record exists in the knowledge records of the knowledge nodes, associating the target knowledge record with the new knowledge node.
Optionally, the step of establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node includes:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes;
and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
Optionally, the step of establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node further includes:
establishing a plurality of labels based on user requirements;
and performing association operation between the knowledge records corresponding to the knowledge nodes and the tags, wherein each knowledge node record is associated with one or more tags.
Optionally, after the step of performing the association operation between the knowledge record corresponding to each knowledge node and the plurality of tags, the method further includes:
when a retrieval instruction sent by a retrieval terminal is received, acquiring a retrieval keyword in the retrieval instruction;
determining a target label and/or a target knowledge node searched by the search terminal based on the search keyword;
and searching the knowledge record associated with the target label and/or the target knowledge node in the knowledge base, and sending the searched knowledge record to the retrieval terminal.
Optionally, after the step of determining the target tag and/or the target knowledge node retrieved by the retrieval terminal based on the retrieval keyword, the method further includes:
and when a correction instruction is received, correcting the retrieved target label and/or target knowledge node based on the correction instruction.
To achieve the above object, a second aspect of the present invention provides an apparatus for optimizing a knowledge base structure, the apparatus comprising:
the creating module is used for creating a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
the judging module is used for determining whether a target knowledge record meeting preset conditions exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base;
and the association module is used for associating the target knowledge record to the new knowledge node if the target knowledge record exists in the knowledge records of the knowledge nodes.
Optionally, the creating module is configured to:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes; and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
Optionally, the apparatus further comprises:
the labeling module is used for establishing a plurality of labels based on user requirements;
and the label association module is used for executing association operation between the knowledge records corresponding to the knowledge nodes and the labels, wherein each knowledge node record is associated with one or more labels.
Optionally, the apparatus further comprises:
the retrieval response module is used for acquiring a retrieval keyword in a retrieval instruction when the retrieval instruction sent by the retrieval terminal is received;
the determining module is used for determining a target label and/or a target knowledge node searched by the searching terminal based on the searching keyword;
and the retrieval module is used for searching the knowledge record associated with the target label and/or the target knowledge node in the knowledge base and sending the searched knowledge record to the retrieval terminal.
Optionally, the apparatus further comprises:
and the correction module is used for correcting the retrieved target label and/or target knowledge node based on the correction instruction when the correction instruction is received.
The embodiment of the invention provides a method for optimizing a knowledge base structure, which comprises the following steps: establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge records corresponding to each knowledge node, determining whether a target knowledge record meeting preset conditions exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base, and associating the target knowledge record with the new knowledge node if the target knowledge record exists. Compared with the prior art, the embodiment of the invention does not need to add a new knowledge record to each new knowledge node, but can associate the existing knowledge records of other knowledge nodes to the new knowledge node to complete the updating of the knowledge base, thereby simplifying the updating process of the knowledge base and effectively reducing the updating cost.
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 described below, it is obvious that the drawings in the following description are only some embodiments of the present invention, and for those skilled in the art, other drawings can be obtained according to the drawings without creative efforts.
FIG. 1 is a flow chart illustrating the steps of a method for optimizing the structure of a knowledge base according to a first embodiment of the present invention;
FIG. 2 is a diagram of the knowledge structure of the knowledge base described in the present invention;
FIG. 3 is a flow chart illustrating the steps of a method for optimizing the structure of a knowledge base according to a second embodiment of the present invention;
FIG. 4 is a flow chart illustrating the steps of a method for optimizing the structure of a knowledge base according to a third embodiment of the present invention;
FIG. 5 is a schematic diagram of program modules of an apparatus for optimizing the structure of a knowledge base according to a fourth embodiment of the present invention;
FIG. 6 is a schematic diagram of program modules of an apparatus for optimizing the structure of a knowledge base according to a fifth embodiment of the present invention;
FIG. 7 is a schematic diagram of program modules of an apparatus for optimizing the structure of a knowledge base according to a sixth embodiment of the present invention.
Detailed Description
In order to make the objects, features and advantages of the present invention more obvious and understandable, the technical solutions in the embodiments of the present invention will be clearly and completely described below with reference to the accompanying drawings in the embodiments of the present invention, and it is apparent that the described embodiments are only a part of the embodiments of the present invention, and not all of the embodiments. All other embodiments, which can be derived by a person skilled in the art from the embodiments given herein without making any creative effort, shall fall within the protection scope of the present invention.
Referring to fig. 1, fig. 1 is a schematic flow chart illustrating steps of a method for optimizing a knowledge base structure according to a first embodiment of the present invention, in which the method for optimizing a knowledge base structure includes:
in the embodiment of the invention, the knowledge content stored in the database or the question bank can be decomposed into two parts, namely a knowledge structure and a knowledge record, wherein the knowledge structure is used for recording the incidence relation between knowledge nodes in the knowledge bank, and the knowledge record is used for recording the specific knowledge content. The knowledge nodes are used for describing the domain to which the knowledge content belongs or a hierarchical classification system of knowledge shared by all domains, each knowledge node in the knowledge base represents a knowledge subject, for example, in the mathematical domain, the knowledge nodes can be divided into 'odd' and 'even' under 'natural number', wherein the 'natural number', 'odd' and 'even' can be used as one knowledge node. The knowledge nodes may also indicate chapters, titles, and the like corresponding to the knowledge points.
The knowledge structure may be a tree structure, a list structure, or the like.
Specifically, the step of establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node in the step 101 specifically includes:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes;
and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
In the embodiment of the invention, each knowledge node is acquired in the knowledge content stored in the preset database, and then the knowledge structure of each knowledge node is established according to the corresponding relationship and classification of each knowledge node, wherein the knowledge structure can be a tree structure or a list structure. And then establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node.
When the knowledge content stored in the database relates to a plurality of disciplines, the constructed knowledge structure may be a plurality of knowledge structures. In addition, the knowledge record itself belongs to an information carrier, and can be characters, videos, pictures and the like, and the knowledge itself is recorded, for example, a segment of characters for describing the concept of the natural number, and the concept of the natural number can be browsed by searching the knowledge node of the 'natural number'.
in the embodiment of the invention, when detecting that a new knowledge node is recorded in the knowledge base, determining whether a target knowledge record meeting a preset condition exists in the knowledge records of each knowledge node, wherein the preset condition comprises that when the association degree of any knowledge node and the new knowledge node is greater than a preset threshold value, or the association degree of any knowledge record and the new knowledge node is greater than a preset threshold value.
It is understood that there is sometimes the same knowledge content between different disciplines in similar or adjacent fields, such as "calculus" which has wide application in the branches of natural sciences, social sciences and applied sciences, including astronomy, mechanics, engineering, economics, etc. Thus, there may be the same knowledge node for different knowledge structures. If the new knowledge node entered in the knowledge base is a "calculus", then it can be determined whether the knowledge record of each knowledge node has a knowledge record associated with the calculus.
And 103, if the target knowledge record exists in the knowledge records of the knowledge nodes, associating the target knowledge record to the new knowledge node.
It can be understood that, for different knowledge nodes, the associated knowledge records are sometimes the same, so that the same knowledge record can be associated to two or more different knowledge nodes in the knowledge base, and a user can browse the same knowledge record when searching for any one knowledge node.
For better understanding of the present invention, please refer to fig. 2, and fig. 2 is a schematic diagram of the knowledge structure of the knowledge base in the present invention. In fig. 2, the knowledge node 2.2 is a new knowledge node, and when it is determined that the knowledge record 1.3 associated with the knowledge node 1.3 can satisfy the preset condition, the knowledge record 1.3 can be associated with the new knowledge node 2.2, and it is not necessary to record the knowledge record corresponding to the knowledge node 2.2 in the knowledge structure 2. The user can browse the knowledge record 1.3 by searching the knowledge node 2.2 or the knowledge node 1.3.
Compared with the prior art, the method for optimizing the structure of the knowledge base provided by the embodiment of the invention determines whether the target knowledge record meeting the preset conditions exists in the knowledge records of each knowledge node when the new knowledge node is generated in the knowledge base, and if the target knowledge record exists, the target knowledge record is associated to the new knowledge node.
Further, referring to fig. 3 based on the first embodiment of the present invention, fig. 3 is a schematic flowchart illustrating steps of a method for optimizing a knowledge base structure according to a second embodiment of the present invention, in which the method for optimizing a knowledge base structure according to the present invention includes:
301, establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
in the embodiment of the present invention, the content described in step 301 is the same as the content described in step 101 in the first embodiment of the present invention, please refer to the first embodiment of the present invention, and details are not described herein again.
in the embodiment of the invention, each knowledge node in the knowledge structure can be cut, the knowledge structure is recorded by adopting a label aggregation mode, and the knowledge structure can support various knowledge structures such as trees, lists, chains and the like.
In order to meet the requirements of users, the users can quickly acquire required knowledge records, and labels such as ' key words in the fourth grade of English ', ' XX necessary examination points ', ' XX teacher ' special subjects ' and the like can be established in a knowledge base.
And 303, executing association operation between the knowledge records corresponding to the knowledge nodes and the plurality of tags, wherein the knowledge nodes are associated with one or more tags.
Wherein the association operation can be executed between each knowledge record and each tag based on the subject type, source, purpose, etc. of each knowledge record. For example, if a knowledge record is associated with a "function," it may be associated with an established "math" label. In addition, the association operation may be executed between each knowledge record and each tag according to a received user trigger operation.
The levels of the labels of the knowledge nodes can be determined according to the node levels of the knowledge nodes, such as a first-level label, a second-level label, a third-level label and the like, and then an aggregation relation is established among the labels according to the levels of the labels and the knowledge structure, for example, the first-level label "college entrance examination" can be associated with the second-level labels such as "college entrance examination mathematics", "college entrance examination language" and "college examination English", and the second-level label "college entrance examination mathematics" can be associated with the third-level labels such as "choice question" and "gap filling question".
The knowledge structure can be evolved and upgraded along with the promotion of business, so that each knowledge record can be associated with one or more tags, the knowledge base can be expanded in various fields by filling content, and meanwhile, the high-efficiency accessibility is kept. For example, "trigonometric function" as a knowledge record, which can be associated with the label "college entrance math"; and may be associated with the label of a teacher "xx lesson series" because it is part of the teacher's lesson hierarchy. Later, the topic is selected as the college entrance examination point, and the topic can be associated with the label of the college entrance examination point.
and 305, if the target knowledge record exists in the knowledge records of the knowledge nodes, associating the target knowledge record with the new knowledge node.
In the embodiment of the present invention, the content described in step 304 to step 305 is the same as the content described in step 102 to step 103 in the first embodiment of the present invention, please refer to the first embodiment of the present invention, and details are not described herein again.
According to the method for optimizing the knowledge base structure, provided by the embodiment of the invention, the plurality of labels are established based on user requirements, and then association operation is executed between each knowledge record and the plurality of labels, wherein each knowledge record is associated with one or more labels, so that the knowledge base can fill contents in various fields conveniently, and meanwhile, the high-efficiency accessibility is kept.
Further, referring to fig. 4 based on the second embodiment of the present invention, fig. 4 is a schematic flowchart illustrating steps of a method for optimizing a knowledge base structure according to a third embodiment of the present invention, in which the method for optimizing a knowledge base structure according to the present invention includes:
step 403, performing association operation between the knowledge records corresponding to the knowledge nodes and the plurality of tags, wherein each knowledge node record is associated with one or more tags;
in the embodiment of the present invention, the contents described in steps 401 to 403 are the same as the contents described in steps 301 to 303 in the second embodiment of the present invention, please refer to the second embodiment of the present invention, and details are not described herein again.
the retrieval terminal can comprise a mobile terminal, a tablet computer, a notebook computer, a desktop computer, an intelligent television and other network terminals.
in the embodiment of the invention, the target label to be searched by the search terminal can be determined by the acquired search keyword through keyword matching; or the knowledge node to be searched by the search terminal can be determined by keyword matching by using the search keyword; or the knowledge node to be searched by the search terminal and the target knowledge node can be determined by keyword matching by using the search keyword.
In the embodiment of the invention, after the target label and/or the target knowledge node to be searched by the search terminal is determined, the knowledge record associated with the target label and/or the target knowledge node can be searched in the knowledge base, and the searched knowledge record is sent to the search terminal.
According to the method for optimizing the knowledge base structure, provided by the embodiment of the invention, when a retrieval instruction sent by a retrieval terminal is received, the retrieval key words in the retrieval instruction are obtained, the target labels and/or the target knowledge nodes retrieved by the retrieval terminal are determined according to the retrieval key words, then the knowledge records related to the target labels and/or the target knowledge nodes are searched in the knowledge base, and the searched knowledge records are sent to the retrieval terminal.
Further, based on the third embodiment of the present invention, in the embodiment of the present invention, after the step of determining the target tag and/or the target knowledge node retrieved by the retrieval terminal based on the retrieval keyword, the method further includes the following steps:
and when a correction instruction is received, correcting the retrieved target label and/or target knowledge node based on the correction instruction.
In the embodiment of the invention, the retrieved target label and/or target knowledge node can be corrected according to the user requirements, so that the label and/or target knowledge node associated with the knowledge record can better meet the user requirements, and the knowledge record can be positioned more accurately. For example, the label "2017-year-compulsory-check-point" is modified to "2018-year-compulsory-check-point", and the like. It will be appreciated that after the tags are modified, the knowledge records associated with the tags before and after modification remain the same.
According to the method for optimizing the knowledge base structure, provided by the embodiment of the invention, when the correction instruction is received, the retrieved knowledge label and/or knowledge node are corrected based on the correction instruction, so that the positioning of the knowledge record is more accurate.
Further, an embodiment of the present invention further provides an apparatus for optimizing a knowledge base structure, please refer to fig. 5, where fig. 5 is a schematic diagram of program modules of the apparatus for optimizing a knowledge base structure according to a fourth embodiment of the present invention, and in the embodiment of the present invention, the apparatus for optimizing a knowledge base structure includes:
a creating module 501, configured to create a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node.
Specifically, the creating module 501 is specifically configured to:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes; and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
A determining module 602, configured to determine whether a target knowledge record meeting a preset condition exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base.
An associating module 603, configured to associate the target knowledge record to the new knowledge node if the target knowledge record exists in the knowledge records of the knowledge nodes.
Compared with the prior art, the device for optimizing the knowledge base structure provided by the embodiment of the invention can realize the following steps: when a new knowledge node is generated in the knowledge base, whether a target knowledge record meeting preset conditions exists in the knowledge records of each knowledge node is determined, and if the target knowledge record exists, the knowledge record corresponding to the target knowledge node is associated to the new knowledge node.
Further, referring to fig. 6 based on a fourth embodiment of the present invention, fig. 6 is a schematic diagram of program modules of an apparatus for optimizing a knowledge base structure according to a fifth embodiment of the present invention, in which the apparatus for optimizing a knowledge base structure according to the present invention includes:
a creating module 501, configured to create a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node.
The labeling module 601 is configured to establish a plurality of labels based on user requirements.
A tag association module 602, configured to perform an association operation between the knowledge record corresponding to each knowledge node and the tags, where the knowledge record associates one or more tags.
A judging module 502, configured to determine whether a target knowledge record meeting a preset condition exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base;
an associating module 503, configured to associate the target knowledge record to the new knowledge node if the target knowledge record exists in the knowledge records of the knowledge nodes.
The device for optimizing the knowledge base structure provided by the embodiment of the invention establishes a plurality of labels based on user requirements, and then performs association operation between each knowledge record and the plurality of labels, wherein each knowledge record is associated with at least one label, so that the knowledge base can fill contents in various fields conveniently, and meanwhile, the high-efficiency accessibility is kept.
Further, referring to fig. 7 based on a fifth embodiment of the present invention, fig. 7 is a schematic diagram of program modules of an apparatus for optimizing a knowledge base structure according to a sixth embodiment of the present invention, in which the apparatus for optimizing a knowledge base structure according to the present invention includes:
a creating module 501, configured to create a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
the labeling module 601 is used for establishing a plurality of labels based on user requirements;
a tag association module 602, configured to perform association operations between the knowledge records corresponding to the knowledge nodes and the tags, where each knowledge node record associates one or more tags;
a retrieval response module 701, configured to, when receiving a retrieval instruction sent by a retrieval terminal, obtain a retrieval keyword in the retrieval instruction;
a determining module 702, configured to determine, based on the search keyword, a target tag and/or a target knowledge node that is retrieved by the retrieval terminal;
a retrieving module 703, configured to search the knowledge record associated with the target tag and/or the target knowledge node in the knowledge base, and send the searched knowledge record to the retrieving terminal.
According to the device for optimizing the knowledge base structure, provided by the embodiment of the invention, when a retrieval instruction sent by a retrieval terminal is received, the retrieval key words in the retrieval instruction are obtained, the target labels and/or the target knowledge nodes retrieved by the retrieval terminal are determined according to the retrieval key words, then the knowledge records related to the target labels and/or the target knowledge nodes are searched in the knowledge base, and the searched knowledge records are sent to the retrieval terminal.
Further, based on the sixth embodiment of the present invention, in the embodiment of the present invention, the apparatus for optimizing a knowledge base structure further includes:
and the correction module is used for correcting the retrieved target label and/or target knowledge node based on the correction instruction when the correction instruction is received.
According to the device for optimizing the knowledge base structure, provided by the embodiment of the invention, when the correction instruction is received, the retrieved knowledge label and/or knowledge node are corrected based on the correction instruction, so that the positioning of the knowledge record is more accurate.
In the several embodiments provided in the present application, 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 modules is merely a logical division, and in actual implementation, there may be other divisions, for example, multiple modules or components may be combined or integrated into another system, or some features may be omitted, or not implemented. 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 modules, and may be in an electrical, mechanical or other form.
The modules described as separate parts may or may not be physically separate, and parts displayed as modules may or may not be physical modules, may be located in one place, or may be distributed on a plurality of network modules. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of the present embodiment.
In addition, functional modules in the embodiments of the present invention may be integrated into one processing module, or each of the modules may exist alone physically, or two or more modules are integrated into one module. The integrated module can be realized in a hardware mode, and can also be realized in a software functional module mode.
The integrated module, if implemented in the form of a software functional module and sold or used as a stand-alone product, may be stored in a computer readable storage medium. Based on such understanding, the technical solution of the present invention may be embodied in the form of a software product, which is stored in a storage medium and includes instructions for causing a computer device (which may be a personal computer, a server, or a network device) to execute all or part of the steps of the method according to the embodiments of the present invention. And the aforementioned storage medium includes: a U-disk, a removable hard disk, a Read-Only Memory (ROM), a Random Access Memory (RAM), a magnetic disk or an optical disk, and other various media capable of storing program codes.
It should be noted that, for the sake of simplicity, the above-mentioned method embodiments are described as a series of acts or combinations, but those skilled in the art should understand that the present invention is not limited by the described order of acts, as some steps may be performed in other orders or simultaneously according to the present invention. Further, those skilled in the art will appreciate that the embodiments described in the specification are presently preferred and that no acts or modules are necessarily required of the invention.
In the above embodiments, the descriptions of the respective embodiments have respective emphasis, and for parts that are not described in detail in a certain embodiment, reference may be made to related descriptions of other embodiments.
In view of the above description of the method and apparatus for optimizing a knowledge base structure provided by the present invention, those skilled in the art will recognize that changes may be made in the method and apparatus for optimizing a knowledge base structure according to the embodiments of the present invention.
Claims (10)
1. A method of optimizing a knowledge base structure, the method comprising:
establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
when a new knowledge node is recorded in the knowledge base, determining whether a target knowledge record meeting a preset condition exists in the knowledge records of each knowledge node;
if the target knowledge record exists in the knowledge records of all the knowledge nodes, the target knowledge record is associated to the new knowledge node;
the step of determining whether a target knowledge record meeting a preset condition exists in the knowledge records of the knowledge nodes comprises:
the degree of association between any knowledge node and the new knowledge node is greater than a preset threshold value, or
And the association degree of any knowledge record and the new knowledge node is greater than a preset threshold value.
2. The method of claim 1, wherein the step of building a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node comprises:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes;
and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
3. The method according to claim 1 or 2, wherein the step of establishing a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node further comprises:
establishing a plurality of labels based on user requirements;
and performing association operation between the knowledge records corresponding to the knowledge nodes and the tags, wherein each knowledge node record is associated with one or more tags.
4. The method of claim 3, wherein the step of performing an association operation between the knowledge record corresponding to each knowledge node and the plurality of tags further comprises:
when a retrieval instruction sent by a retrieval terminal is received, acquiring a retrieval keyword in the retrieval instruction;
determining a target label and/or a target knowledge node searched by the search terminal based on the search keyword;
and searching the knowledge record associated with the target label and/or the target knowledge node in the knowledge base, and sending the searched knowledge record to the retrieval terminal.
5. The method of claim 4, wherein the step of determining the target label and/or target knowledge node retrieved by the retrieval terminal based on the retrieval keyword further comprises:
and when a correction instruction is received, correcting the retrieved target label and/or target knowledge node based on the correction instruction.
6. An apparatus for optimizing knowledge base structure, the apparatus comprising:
the creating module is used for creating a knowledge base according to the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node;
the judging module is used for determining whether a target knowledge record meeting preset conditions exists in the knowledge records of each knowledge node when a new knowledge node is recorded in the knowledge base; the step of determining whether a target knowledge record meeting a preset condition exists in the knowledge records of the knowledge nodes comprises:
the degree of association between any knowledge node and the new knowledge node is greater than a preset threshold value, or
The association degree of any knowledge record and the new knowledge node is greater than a preset threshold value;
and the association module is used for associating the target knowledge record to the new knowledge node if the target knowledge record exists in the knowledge records of the knowledge nodes.
7. The apparatus of claim 6, wherein the creation module is to:
collecting all knowledge nodes in a preset database, and constructing knowledge structures of all knowledge nodes; and establishing the knowledge base based on the knowledge structure of each knowledge node and the knowledge record corresponding to each knowledge node, wherein the type of the knowledge record comprises one or more items of characters, videos and pictures.
8. The apparatus of claim 6 or 7, wherein the apparatus further comprises:
the labeling module is used for establishing a plurality of labels based on user requirements;
and the label association module is used for executing association operation between the knowledge records corresponding to the knowledge nodes and the labels, wherein each knowledge node record is associated with one or more labels.
9. The apparatus of claim 8, wherein the apparatus further comprises:
the retrieval response module is used for acquiring a retrieval keyword in a retrieval instruction when the retrieval instruction sent by the retrieval terminal is received;
the determining module is used for determining a target label and/or a target knowledge node searched by the searching terminal based on the searching keyword;
and the retrieval module is used for searching the knowledge record associated with the target label and/or the target knowledge node in the knowledge base and sending the searched knowledge record to the retrieval terminal.
10. The apparatus of claim 9, wherein the apparatus further comprises:
and the correction module is used for correcting the retrieved target label and/or target knowledge node based on the correction instruction when the correction instruction is received.
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Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270238A (en) * | 2011-08-11 | 2011-12-07 | 北京龙戴特信息技术有限公司 | Method and device for establishing continuation of Chinese knowledge points |
| CN102682107A (en) * | 2012-05-08 | 2012-09-19 | 《中国学术期刊(光盘版)》电子杂志社 | Academic knowledge expressing method based on knowledge network node mode |
| CN103559269A (en) * | 2013-11-04 | 2014-02-05 | 北京中搜网络技术股份有限公司 | Knowledge recommending method for mobile news subscription |
| CN104462227A (en) * | 2014-11-13 | 2015-03-25 | 中国测绘科学研究院 | Automatic construction method of graphic knowledge genealogy |
| CN105809594A (en) * | 2016-03-11 | 2016-07-27 | 武汉天量数据技术有限公司 | Flexible knowledge point system construction method and system |
| CN105893476A (en) * | 2016-03-29 | 2016-08-24 | 上海智臻智能网络科技股份有限公司 | Intelligent questioning and answering method, knowledge base optimization method and device, and intelligent knowledge base |
| CN105989097A (en) * | 2015-02-12 | 2016-10-05 | 北京仿真中心 | Ontology-based knowledge base query method and system |
| CN106503074A (en) * | 2016-09-30 | 2017-03-15 | 上海高顿教育培训有限公司 | A kind of exercise question classification method |
| CN107798123A (en) * | 2017-11-10 | 2018-03-13 | 上海智臻智能网络科技股份有限公司 | Knowledge base and its foundation, modification, intelligent answer method, apparatus and equipment |
Family Cites Families (1)
| Publication number | Priority date | Publication date | Assignee | Title |
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-
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- 2018-04-27 CN CN201810391778.8A patent/CN108536872B/en active Active
Patent Citations (9)
| Publication number | Priority date | Publication date | Assignee | Title |
|---|---|---|---|---|
| CN102270238A (en) * | 2011-08-11 | 2011-12-07 | 北京龙戴特信息技术有限公司 | Method and device for establishing continuation of Chinese knowledge points |
| CN102682107A (en) * | 2012-05-08 | 2012-09-19 | 《中国学术期刊(光盘版)》电子杂志社 | Academic knowledge expressing method based on knowledge network node mode |
| CN103559269A (en) * | 2013-11-04 | 2014-02-05 | 北京中搜网络技术股份有限公司 | Knowledge recommending method for mobile news subscription |
| CN104462227A (en) * | 2014-11-13 | 2015-03-25 | 中国测绘科学研究院 | Automatic construction method of graphic knowledge genealogy |
| CN105989097A (en) * | 2015-02-12 | 2016-10-05 | 北京仿真中心 | Ontology-based knowledge base query method and system |
| CN105809594A (en) * | 2016-03-11 | 2016-07-27 | 武汉天量数据技术有限公司 | Flexible knowledge point system construction method and system |
| CN105893476A (en) * | 2016-03-29 | 2016-08-24 | 上海智臻智能网络科技股份有限公司 | Intelligent questioning and answering method, knowledge base optimization method and device, and intelligent knowledge base |
| CN106503074A (en) * | 2016-09-30 | 2017-03-15 | 上海高顿教育培训有限公司 | A kind of exercise question classification method |
| CN107798123A (en) * | 2017-11-10 | 2018-03-13 | 上海智臻智能网络科技股份有限公司 | Knowledge base and its foundation, modification, intelligent answer method, apparatus and equipment |
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