DocumentCode
3402389
Title
Approximate Metrics for Autonomous Semantic Web Ontology Merging
Author
Richardson, Bartley ; Mazlack, Lawrence J.
Author_Institution
Dept. of Electr. Eng. & Comput. Sic., Cincinnati Univ., OH
fYear
2005
fDate
25-25 May 2005
Firstpage
1014
Lastpage
1019
Abstract
The semantic Web is the next step in the Internet´s evolution. The existing Web contains a considerable amount of data; most is weakly structured. Broadly accessing the data is difficult. Previously unseen data cannot be easily autonomously understood with out a consistent semantic framework. Viewing and organizing data using shared ontologies is essential for both sharing data and for Web site interoperability. Full autonomous or semi-autonomous discovery and development of ontologies is the only feasible way to transition the existing Web to the semantic Web. One strategy is to merge existing, vetted ontologies. The pre-merger ontologies would likely be similar in some respects and different in others. When comparing ontologies, a necessarily imprecise, approximate similarity metric will be necessary. Possibly, soft computing will provide useful tools
Keywords
Web sites; data mining; fuzzy set theory; information retrieval; ontologies (artificial intelligence); open systems; semantic Web; Internet; Web site interoperability; approximate metrics; autonomous discovery; autonomous semantic Web ontology merging; data access; data organization; data sharing; data viewing; ontology development; semantic framework; semiautonomous discovery; similarity metric; Artificial intelligence; Data mining; Internet; Laboratories; Merging; Ontologies; Organizing; Semantic Web; Web pages; Web services;
fLanguage
English
Publisher
ieee
Conference_Titel
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location
Reno, NV
Print_ISBN
0-7803-9159-4
Type
conf
DOI
10.1109/FUZZY.2005.1452533
Filename
1452533
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