Domain Knowledge Structure Cognition:An Applicability Analysis in Big Data Environments
[Purpose/Significance]In big data environments,knowledge is ubiquitous,fragmented and large in scale.Recognizing and grasping the existing domain knowledge structures can provide a reference for scientific and efficient domain knowledge organization.[Method/Process]The cognition of domain knowledge structure helped explore the relationships between knowledge units.It showed the principles,connotations,and frameworks of domain knowledge formed by the combinations.Knowledge organized from different perspec-tives,contexts and applications could present different knowledge structures.The Chinese Library Classification and Chinese Thesaurus has provided hierarchical,equivalent,and related relationships between knowledge units.The former one focused on knowledge category construction to build a tree-like knowledge system,while the latter connected thematic knowledge through concept coordination,related relationships,and multiple member-ships,forming a semantic network to express topic related and extended knowledge.The semantic knowledge associative structure constructed the<Subject,Predicate,Object>triples to form a semantic network.These networks expressed knowledge related to category affiliation,attributes,and semantic relationships.And they represented implicit knowledge through axiomatic reasoning.[Result/Conclusion]In the big data environment,a tree-like hierarchical structure with multiple affiliations and cross-connections is constructed to represent the category attribution of ubiquitous knowledge.The thematic approach achieves the coarse-grained and conceptual representation of fragmented and fine-grained knowledge,while the semantic relations are more explicit and spe-cific.Semantic associative knowledge structures are more flexible and extensible,which can provide reasoning knowledge.The domain knowledge structures are evolving towards being suitable for knowledge organization in big data environments.
万方数据
