Agglomerative clustering based index construction for search engines using agents

The information on World Wide Web is growing at an exponential rate; therefore search engines are required to index the downloaded web documents. Indexing in search engines is an active area of current researches. The main aim of search engine is to provide best relevant documents to the users in minimum possible time. The major issue for performances of Web search engine is to provide efficient and fast access to the index. Indexing is performed on the web pages after they have been collected into the web page repository by the crawling agent community. Web search engines use inverted file index that consists of an array of the posting lists where each posting list is associated with a term and contains the term as well as the identifiers of the documents containing the term. Since the document collected by crawling agent stored in web page repository and indexer agent extract the document from page repository. Where the matcher agent that will take all the document extracted by the indexer agent for checking the document similarity between them and store the same similarity document in min cluster. In this paper, we presents Agglomerativehierarchical clustering algorithm which aims at partitioning the set of documents into ordered cluster so that the document with in the same cluster are similar and are being assigned the closer document identifiers.