A decentralized search engine for dynamic Web communities

作者:Daze Wang, Quincy Chi Kwan Tse, Ying Zhou

摘要

Currently, most Web search engines perform search on corpus comprising nearly entire content of the Web. The same centralized search service can be performed on a single site as well. Nonetheless, there is little research on community-wide search. This paper presents a peer-to-peer search engine ComSearch. ComSearch is designed to provide small- and middle-scale online communities—the ability to perform text search within the community. Communities are formed in a self-organizing style. P2P IR system may suffer unnecessary internal traffic in answering a multi-term query. In this paper, we propose several techniques to optimize the multi-term query process. The simulation results show that our proposed algorithms have good scalability. Compared with baseline approach, our improved algorithm can reduce the communication cost by about two orders of magnitude in the best case. We also deploy the system in a small-scale network and conduct a series of experiments to estimate the actual query response time as well as to investigate the data movement effect caused by node joining. Experimental results show that multiple data movements are quite common during network expansion. However, the percentage of multiple data movements decreases when a network is getting stable after the initial frequent joining activities. This provides possibilities for improvement on P2P data movement management.

论文关键词:Distributed hash table, Bloom filter, Information retrieval, Community level search, Web feed

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论文官网地址:https://doi.org/10.1007/s10115-009-0270-7