Abstract
AbstractThe state-of-the-art keyword search system for structured P2P systems is built on the distributed inverted index. However, Distributed inverted index by keywords may incur significant bandwidth for executing more complicated search queries such as multiple-attribute queries. In order to reduce query overhead, KSS (Keyword Set Search) by Gnawali partitions the index by a set of keywords. However, a KSS index is considerably larger than a standard inverted index, since there are much more word sets than individual words. And the insert overhead and storage overhead are obviously unacceptable for full-text search on a collection of documents. In this paper, we presents pKSS, a P2P keyword search system that that adopts term ranking approach such as TFIDF and exploits the relationship information between query keywords to improve performance of P2P keyword search. Experimental results clearly demonstrated that the improved keyword search is more efficient than KSS index in insert overhead and storage overhead, and much less than standard inverted index on bandwidth costs for a query.
Published Version
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