Fragmented knowledge intelligent aggregation method

An aggregation method and fragmentation technology, applied in the field of intelligent aggregation of fragmented knowledge, can solve the problems of coarse granularity, too single, undiscovered patent publications, etc., and achieve the effect of high description accuracy and accurate personalized recommendation.

Active Publication Date: 2018-07-13
TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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  • Abstract
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  • Claims
  • Application Information

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Problems solved by technology

[0004] However, the existing technology has the following disadvantages: On the one hand, the current online education based on MOOCs, micro-classes, quality courses, etc., the organization of course content is still traditional, structured, and systematic, and the granularity is too coarse. , too single, it is necessary to realize the refinement, multi-dimensional and personalized organization of knowledge through effective content spli

Method used

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  • Fragmented knowledge intelligent aggregation method
  • Fragmented knowledge intelligent aggregation method
  • Fragmented knowledge intelligent aggregation method

Examples

Experimental program
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Example Embodiment

[0042] Example 1

[0043] An intelligent aggregation method of fragmented knowledge, the steps are as follows:

[0044] Step 1. Define the knowledge element ontology:

[0045] The knowledge is reasonably fragmented and divided into a suitable granularity with the smallest set of knowledge points, that is, the knowledge element. At the same time, the granularity is a knowledge element with a complete semantic unit, which can then extract a concept, a theorem, a formula, a data, or an experimental process, etc., to the smallest knowledge unit that can explain a certain knowledge.

[0046] The structure of Knowledge Unit Ontology (KUO) can be described as the following four-tuple:

[0047] K=(C,P,M,R) (1)

[0048] Among them, K represents the ontology structure of knowledge element, C represents a certain domain concept, P and M are a set of attributes and methods on concept C, and R is a set of relationships established on C with other concepts.

[0049] Step 2. Define the association aggr...

Example Embodiment

[0073] Example 2

[0074] An intelligent aggregation method of fragmented knowledge, the steps are as follows:

[0075] Step 1. Define the knowledge element ontology:

[0076] The knowledge is reasonably fragmented and divided into a suitable granularity with the smallest set of knowledge points, that is, the knowledge element. At the same time, the granularity is a knowledge element with a complete semantic unit, and the knowledge element ontology structure of the knowledge element is described as the following four-tuple:

[0077] K=(C,P,M,R) (1);

[0078] Among them, K represents the ontology structure of knowledge element, C represents a certain domain concept, P and M are a set of attributes and methods on concept C, and R is a set of relationships with other concepts based on C;

[0079] Step 2. Define the association aggregation of fragmented ontology:

[0080] In order to further clarify the semantic content and semantic relation of the ontology structure of the knowledge element...

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Abstract

The invention relates to a fragmented knowledge intelligent aggregation method. The method comprises the steps that step 1, knowledge element ontologies are defined; step 2, fragmented knowledge ontology associated aggregation is defined; step 3, associated aggregation rules based on ontology implication are established; step 4, the determination of aggregation associated rules is conducted; step5, the determination of fragmented knowledge associated rules based on the knowledge element ontologies is conducted; step 6, fragmented knowledge aggregation associated discovery is conducted; step 7, fragmented knowledge aggregation is achieved. According to the method, the associated relationship between two or more knowledge element ontologies is determined through supporting and confidence level determination, and fragmented knowledge aggregation is achieved through a strong associated method; fragmented knowledge characteristics are analyzed by the method, facing the demands of online study, original solid knowledge structures are repartitioned and dynamically aggregated into a knowledge cluster with a self-organizing capability to finally complete fragmented knowledge aggregation, and learners are guided to fully utilize fragmented time to accurately acquire meaningful knowledge contents.

Description

technical field [0001] The invention belongs to the field of artificial intelligence, in particular to an intelligent aggregation method of fragmented knowledge. Background technique [0002] In the "Internet +" era, the deep integration of information technology and education and teaching has produced a series of new online education models represented by micro-classes and MOOCs. Learning, mobile learning and other needs. With the widespread application of new media and smart media devices, more and more people tend to use smart mobile terminals such as smartphones and tablets for reading and learning. According to the "2016 White Paper on Online Education Users" released by Sina The survey shows that 45% of users use online education products in fragmented time. It can be seen that the popularity of this new fragmented learning method marks the arrival of the era of fragmentation. Fragmented learning breaks through the constraints of time and space, and at the same time...

Claims

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Application Information

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IPC IPC(8): G06F17/30
CPCG06F16/35G06F16/367
Inventor 梁琨张翼英史艳翠王聪叶子楼贤拓
Owner TIANJIN UNIVERSITY OF SCIENCE AND TECHNOLOGY
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