Semantic Ontology Merging for Effective Information Retrieval System
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(Sprache: Englisch)
Traditional Information Retrieval systems users are not able to get semantic description of the information needed by them, so Intelligent Information Retrieval (IIR) systems are used to find out the more relevant information. Semantic web represents a...
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Traditional Information Retrieval systems users are not able to get semantic description of the information needed by them, so Intelligent Information Retrieval (IIR) systems are used to find out the more relevant information. Semantic web represents a technique for getting semantic information from the particular domain ontology. It involves retrieving of the data semantically through domain ontology's based on user queries. Semantic web based Searching mechanisms which will perform search on the reformed query and display the list of matched documents. In past, various ontology merging algorithms had been anticipated based on the concept of removing overlaps. Here, a new approach of ontology merging is proposed based on the semantic analysis that deals with same domain specific ontology's. Proposed algorithm is fully automated merging algorithm that uses the class semantics, property semantics using Wordnet. The need of ontology merging that will help to maintain ontology's andthe interaction with these ontology's will increase.
Autoren-Porträt von Ankit Vidyarthi, Ankita Sharma
Vidyarthi, AnkitAnkit Vidyarthi Ph.D(p),M.Tech(CSE), B.Tech(CSE). His research interest includes Machine Learning, Soft Computing, Medical Imaging and Data Mining. He has published several research papers in IEEE,Springer.Ankita Sharma M.Tech(CSE),B.Tech(CSE). Her interest areas are Intelligent Information Retrieval,Semantic Web. she has published several papers
Bibliographische Angaben
- Autoren: Ankit Vidyarthi , Ankita Sharma
- 2014, 112 Seiten, Maße: 22 cm, Kartoniert (TB), Englisch
- Verlag: LAP Lambert Academic Publishing
- ISBN-10: 3659554979
- ISBN-13: 9783659554971
Sprache:
Englisch
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