NDLI: The Ontology Based Semantic Evaluating Method in LAV

Content Provider	IEEE Xplore Digital Library
Author	Fei Ren Hao Liang Liang Hu Wanli Zuo
Copyright Year	2009
Abstract	The Web has been dramatically deepened by the Deep Web, which the traditional information fusion system shows disability to integrate. The myriad information hidden behind the Deep Web attracts the considerable attention from the researchers. The key element in a Deep Web information fusion system is the data source modeling problem, which determine the whole technical method of the whole system. The query interfaces provided by the Deep Web are the clues to disclose the hidden schemas. But the complicated semantic relationships in the query interfaces lead to the low generality and ability of local as view (LAV) method in the traditional information fusion system. An approach of evaluating the semantic relationships between the attributes in the query interfaces by utilizing WordNet, a typical Ontology technique, is presented in this paper. The semantic relationships between semantic related attributes are evaluated by the semantic calculating method of WordNet. The meaningless attributes is instantiated by instance information embedded in the interfaces in order to attach correlated semantic information. The experiment is carried out in the real life domains, and the result shows the efficiency of Ontology based Semantic Evaluating Method in LAV.
Starting Page	167
Ending Page	170
File Size	268038
Page Count	4
File Format	PDF
ISBN	9780769536149
DOI	10.1109/PACCS.2009.124
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2009-05-16
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Knowledge engineering query interface information fusion Circuits Laboratories Educational technology Ontologies Educational institutions WordNet Computer science Databases local as view Search engines Deep Web Computer science education ontology
Content Type	Text
Resource Type	Article

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