Intelligent Agent Based Semantic Web in Cloud Computing Environment
This work addresses the need for meaningful web search for users, though it appears incremental as it builds on existing semantic search engines and meta-search concepts.
The paper tackles the problem of ineffective keyword-based web search by proposing SemanTelli, a meta-semantic-search engine that fetches results from multiple semantic search engines using intelligent agents in a cloud environment, aiming to provide more efficient and relevant search outcomes.
Considering today's web scenario, there is a need of effective and meaningful search over the web which is provided by Semantic Web. Existing search engines are keyword based. They are vulnerable in answering intelligent queries from the user due to the dependence of their results on information available in web pages. While semantic search engines provides efficient and relevant results as the semantic web is an extension of the current web in which information is given well defined meaning. MetaCrawler is a search tool that uses several existing search engines and provides combined results by using their own page ranking algorithm. This paper proposes development of a meta-semantic-search engine called SemanTelli which works within cloud. SemanTelli fetches results from different semantic search engines such as Hakia, DuckDuckGo, SenseBot with the help of intelligent agents that eliminate the limitations of existing search engines.