Multi Agent Architecture for Search Engine

The process of retrieving information is becoming ambiguous day by day due to huge collection of documents present on web. A single keyword produces millions of results related to given query but these results are not up to user expectations. The search results produced from traditional text search engines may be relevant or irrelevant. The underlying reason is Web documents are HTML documents that do not contain semantic descriptors and annotations. The paper proposes multi agent architecture to produce fewer but personalized results. The purpose of the research is to provide platform for domain specific personalized search. Personalized search allows delivering web pages in accordance with user’s interest and domain. The proposed architecture uses client side as well server side personalization to provide user with personalized fever but more accurate results. Multi agent search engine architecture uses the concept of semantic descriptors for acquiring knowledge about given domain and leading to personalized search results. Semantic descriptors are represented as network graph that holds relationship between given problem in form of hierarchy. This hierarchical classification is termed as Taxonomy.