Customized Ontology model for Web Information Gathering using Clustering
Journal Title: IOSR Journals (IOSR Journal of Computer Engineering) - Year 2014, Vol 16, Issue 4
Abstract
Abstract: The explosion of data leads to the problem on how information should be retrieved accurately and effectively. To address this issue, ontology’s are widely used to represent user profiles in personalized web information gathering. As a model for knowledge description and formalization, ontology’s are widely used to represent user profiles in personalized web information gathering. When representing user profiles, many models have utilized only knowledge from either a global knowledge base or local knowledge base. Ontology model learns user profiles from both a world knowledge base and local knowledge base. A non-content based customized ontology model is proposed for knowledge representation and reasoning over user profiles. This model generates user Local Instance Repository which includes non-content based descriptors referring to the subjects. This model has improvement over former models in hit/miss ratio, precision and recall parameters.
Authors and Affiliations
Archana Chaugule, , Tushar Ghorpade , Puja Padiya
Keywords
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- EP ID EP94354
- DOI 10.9790/0661-16418086
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