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
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;
Conference_Titel :
Fuzzy Systems, 2005. FUZZ '05. The 14th IEEE International Conference on
Conference_Location :
Reno, NV
Print_ISBN :
0-7803-9159-4
DOI :
10.1109/FUZZY.2005.1452533