TY - GEN
T1 - SUSHI
T2 - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
AU - Thomas, Paul
AU - Shokouhi, Milad
PY - 2009
Y1 - 2009
N2 - Modern techniques for distributed information retrieval use a set of documents sampled from each server, but these samples have been underutilised in server selection. We describe a new server selection algorithm, SUSHI, which unlike earlier algorithms can make full use of the text of each sampled document and which does not need training data. SUSHI can directly optimise for many common cases, including high precision retrieval, and by including a simple stopping condition can do so while reducing network traffic. Our experiments compare SUSHI with alternatives and show it achieves the same effectiveness as the best current methods while being substantially more efficient, selecting as few as 20% as many servers.
AB - Modern techniques for distributed information retrieval use a set of documents sampled from each server, but these samples have been underutilised in server selection. We describe a new server selection algorithm, SUSHI, which unlike earlier algorithms can make full use of the text of each sampled document and which does not need training data. SUSHI can directly optimise for many common cases, including high precision retrieval, and by including a simple stopping condition can do so while reducing network traffic. Our experiments compare SUSHI with alternatives and show it achieves the same effectiveness as the best current methods while being substantially more efficient, selecting as few as 20% as many servers.
KW - Document samples
UR - http://www.scopus.com/inward/record.url?scp=72449180895&partnerID=8YFLogxK
U2 - 10.1145/1571941.1572014
DO - 10.1145/1571941.1572014
M3 - Conference contribution
SN - 9781605584836
T3 - Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
SP - 419
EP - 426
BT - Proceedings - 32nd Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, SIGIR 2009
Y2 - 19 July 2009 through 23 July 2009
ER -