OCS — A system for optimizing, clustering and summarizing web search results using intelligent agents

Internet has brought a major revolution in social community especially among researchers. Number of commercial search engines has emerged with lots of information available online to end user. A Web surfer who wishes to surf the contents available online faces quite large number of problems. This paper in turn addresses three aspects, which we call term as OCS system. The proposed system or study analyzes the duplicates occurring in the content and link levels at first step, there by producing an optimized result. At second level, the optimized contents are clustered using top frequent clustering approach by identifying an optimal threshold. Finally the clustered contents are summarized using extraction process at query level and anchor text level. We take Google search engine and the results given by them for our case study to implement the system effectively.