Title: An improved semantic information searching scheme based multi-agent system and an innovative similarity measure

Authors: Djamel Nessah; Okba Kazar

Addresses: Computer Science Department, Abbes Laghrour University, Khenchela 40002, Algeria ' Computer Science Department, Laboratoire d'Informatique Intelligente, Mohamed Khider University, Biskra 07000, Algeria

Abstract: The key task for the web, namely, web searches, is evolving towards some novel form of semantic web search. In fact, most information retrieval systems are based on static vectors representations. Two major difficulties when a researcher uses current information retrieval systems are how to filter out irrelevant documents, and how to discover latest or more significant documents. Recently a very promising approach to semantic web search is based on combining standard web pages and search queries with ontological background knowledge. In this perspective we will describe a model to hold a document's noise, and incompleteness. For this, we merge a syntactic keyword search with purely semantic search based domain ontology and a multi-agent system to solve such distributed problems. Then we perform a ranking algorithm on returned documents, and we propose a new semantic similarity measure between concepts based on the WordNet taxonomy structure.

Keywords: semantic information search; multi-agent systems; MAS; agent-based systems; semantic web; web languages; ontology; semantic annotation; metadata; inference engine; similarity measures; WordNet taxonomy; web search; information retrieval; ranking algorithms; document filtering.

DOI: 10.1504/IJMSO.2013.058411

International Journal of Metadata, Semantics and Ontologies, 2013 Vol.8 No.4, pp.282 - 297

Received: 11 Mar 2013
Accepted: 03 Oct 2013
Published online: 14 Oct 2014 *

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