Query optimizing on a decentralized web search engine

  • Authors:
  • Daze Wang;Ying Zhou;Joseph Davis

  • Affiliations:
  • University of Sydney, Australia;University of Sydney, Australia;University of Sydney, Australia

  • Venue:
  • Proceedings of the 2007 ACM symposium on Applied computing
  • Year:
  • 2007

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Abstract

Currently, most web search engines perform search on nearly a whole copy of the web corpus. There are also tools to add search functionality to a single site. Nonetheless, there is little research into search related to online communities: set of related websites or weblogs. To fill this gap, a peer-to-peer search engine is presented in this paper. This p2p search engine is designed to provide small- and middle-scale online communities such as blog sites and news sites the ability to perform text search within the community. It organizes nodes on a Distributed Hash Table (DHT) based peer-to-peer network. Communities are formed in a self-organizing style. P2P IR systems may cause increased internal traffic among nodes in answering a multi-term query. In this paper, we focused on this issue and proposed several techniques to optimize the multi-term query process in a P2P framework. Our proposed algorithms are evaluated by simulation. The simulation results show that our proposed algorithms have good scalability and can improve performance of the system by about two orders of magnitude in the best case.