Paper Info
Title
Query optimizing on a decentralized web search engine
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.
Year
DOI
Venue
2007
10.1145/1244002.1244194
SAC
Keywords
Field
DocType
query optimizing,decentralized web search engine,search functionality,multi-term query,p2p ir system,text search,p2p framework,p2p search engine,peer-to-peer search engine,web search engine,middle-scale online community,proposed algorithm,information retrieval,query optimization,p2p,self organization,distributed hash table,search engine
Web search engine,Web search query,Query expansion,Information retrieval,Computer science,Web query classification,Beam search,Search engine indexing,Search analytics,Database,Spamdexing
Conference
ISBN
Citations 
PageRank 
1-59593-480-4
0
0.34
References 
Authors
4
3
Name
Order
Citations
PageRank
Daze Wang170.84
Ying Zhou2394.81
Joseph Davis3433.77