Retrieval of Fresh Information Using P2P Network

The fast development of the World Wide Web and Dynamic nature makes it a challenge for searching and retrieving of information that is more recent .The WWW is a rapidly growing and changing information source. Its growth and change rates make the task of finding recent information harder. The exponentially growing information published on the Web relies largely on a few major search engines like Google to be brought to the public nowadays. In fact, the increasing dynamics of the information distributed on the Internet challenge the flexibility of these centralized search engines. However, such an engine is not suitable for fresh information retrieval because it spends a long time to collect web pages by using a web robot (or crawler). In the other hand, there are some distributed search engines such as Cooperative Search Engine (CSE), and so on. However, these distributed search engines are able to update in a very short time, e.g. a few minutes. But it has more communication delay. In this paper, in order to reduce the delay we proposed a P2P Web search that connects an a-priori unlimited number of peers, each of which maintains a personal local database and a local search facility. Each peer posts a small amount of metadata to a physically distributed directory layered on top of a DHT-based overlay network that is used to efficiently select promising peers from across the peer population that can best locally execute a query. Further usage of Apriori algorithm and Page Rank algorithm improves mining of frequently viewed documents to greater extent. We also uses Textual Entailment approach for searching a relevant document for a given keyword ie) to retrieve not only textual documents that have specified keywords, but also to discover semantically equivalent or entailed documents from given keywords.