Study On P2P-Based Distributed Search Engine

The rapid growth of Internet leads to explosion of information. How to get valuable information on the Internet rapidly and accurately is more and more important. The advent of search engine provides the users great convenience when they retrieve information on Internet. The rapidness and accurateness of information retrieval makes search engine one of the most important and popular application.However, there are two drawbacks in current search engines. First, the search depth is not ideal. Search engines obtain information on Internet via web crawler, so they cannot get the shared information stored in users' personal computer. Second, search engines rank pages based on keywords and hyperlink analysis. And the users' feedback information is not taken into consideration.This paper brings P2P technology into search engine and proposes a model of P2P-Based Distributed Search Engine and a new ranking algorithm. First, the paper designs a model of P2P-Based Distributed Search Engine. There is no directory server in this model. Every computer is as a peer. Peers publish the index of local resource on P2P network to provide search service for other peers. Therefore the shared information stored in users' personal computer can be retrieved. By this way, the search depth is improved. Then the paper proposes a new ranking algorithm based on the model. The ranking algorithm uses relevance as the basic ranking factor. And use popularity factor and friendliness factor to optimize ranking result. Relevance is the value of query request and document. Popularity factor reflects the resource's popularity in the network. Friendliness factor reflects the users' interest. The ranking algorithm utilizes users' feedback information to optimize ranking result. Therefore more accurate result can be presented to specific user.