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Founder International Ontology-based Knowledge Management System To Build

Posted on:2011-08-10Degree:MasterType:Thesis
Country:ChinaCandidate:Y WangFull Text:PDF
GTID:2208330335497383Subject:Software engineering
Abstract/Summary:PDF Full Text Request
As the Founder International continues to develop, it is more and more urgent to solve the problem of Knowledge Island through building up Knowledge Management System. However, on the aspect of knowledge management, there exist problems of low recall ratio and low precision ratio with retrieval techniques which are based on keyword matching due to heterogeneity of information formats, semantic multiplicity and inadequacy of information relationship. Founder International Knowledge Management System has effectively improved the utilization of knowledge, through the use of ontology technology to translate knowledge, according to its meaning, to symbols that computers can understand.Firstly, the current situation of Knowledge Island facing Founder International is analyzed, making it clear that it is meaningful and essential to build up Knowledge Management System. Based on this, specific business requirements of knowledge management are then discussed after comparing advantages and disadvantages of currently existing domestic and foreign Knowledge Management System and considering Founder International's actual state as a software enterprise. Secondly, the overall system architecture is discussed under ontology technology, and such core subsystems as knowledge acquisition and retrieval are carefully designed in detail. The focus of discussion is ontology modeling of knowledge through ontology model in the field of software constructed by Protege, and ontology-based knowledge reasoning and retrieving by Jena. Finally, the comparison is made between the system and products of the kind, and the future of ontology technique's application in knowledge management is discussed.
Keywords/Search Tags:Knowledge Management, Knowledge Management System, Ontology, Knowledge Reasoning, Knowledge Retrieval
PDF Full Text Request
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