Proceedings of the 20th ACM Conference on Hypertext and Hypermedia 2009
DOI: 10.1145/1557914.1557974
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Sixearch.org 2.0 peer application for collaborative web search

Abstract: Sixearch.org is a peer application for social, distributed, adaptive Web search, which integrates the Sixearch.org protocol, a topical crawler, a document indexing system, a retrieval engine, a P2P network communication system, and a contextual learning system. With a single click, the Sixearch.org application will build your personal Web collection. You can search not only your collection, but also other Sixearch peers. When you submit a query, your Sixearch agent will determine which peers are best suited to… Show more

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Cited by 9 publications
(10 citation statements)
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“…This significantly reduces network traffic for popular queries while maintaining a global result cache that adapts in real-time to submitted queries. (Bawa et al, 2003;Sripanidkulchai et al, 2003;Crespo and Garcia-Molina, 2004;Klampanos and Jose, 2004;Akavipat et al, 2006;Klampanos and Jose, 2007;Lu and Callan, 2007;Nguyen et al, 2008;Lele et al, 2009;Papapetrou et al, 2010;Tirado et al, 2010) When using local indices, keeping peers with similar content close to each other can make query processing more efficient. Instead of sending a query to all peers it can be sent to a cluster of peers that covers the query's topic.…”
Section: Involving Fewer Peers During Index Look-ups By Global Replicmentioning
confidence: 99%
See 2 more Smart Citations
“…This significantly reduces network traffic for popular queries while maintaining a global result cache that adapts in real-time to submitted queries. (Bawa et al, 2003;Sripanidkulchai et al, 2003;Crespo and Garcia-Molina, 2004;Klampanos and Jose, 2004;Akavipat et al, 2006;Klampanos and Jose, 2007;Lu and Callan, 2007;Nguyen et al, 2008;Lele et al, 2009;Papapetrou et al, 2010;Tirado et al, 2010) When using local indices, keeping peers with similar content close to each other can make query processing more efficient. Instead of sending a query to all peers it can be sent to a cluster of peers that covers the query's topic.…”
Section: Involving Fewer Peers During Index Look-ups By Global Replicmentioning
confidence: 99%
“…In a similar vein Tsoumakos and Roussopoulos (2003) introduce adaptive probabilistic search where each peer maintains a probabilistic routing table for each query that either originated from it or travelled through it. The initial peer that submits a query broadcasts it to all its neighbours, but from there on the query message is forwarded only to (2008); Lele et al (2009) the neighbour that has the highest probability of obtaining results based on past feedback. Zeinalipour-Yazti et al (2004) build upon this and propose a mechanism where peers actively build profiles of neighbouring peers based on the most recent queries they responded to, similar to Joseph (2002).…”
Section: Involving Fewer Peers During Query Processing By Clusteringmentioning
confidence: 99%
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“…Created by SUN in 2001, JXTA has iterated through successive revisions during its 10 years of history, slowly gaining popularity, with over 2,700,000 downloads and more than 120 active projects. Such projects range from real-time collaboration or web search to remote robot control (Connex, 2007;Matsuo K, 2009;Lele N., 2009).…”
Section: Introductionmentioning
confidence: 99%
“…Created by SUN in 2001, JXTA has iterated through successive revisions during its 10 years of history, slowly gaining popularity, with over 2,700,000 downloads and more than 120 active projects. Such projects range from real-time collaboration [2] to remote robot control [3] or collaborative web search [4].…”
Section: Introductionmentioning
confidence: 99%