Sciweavers

Share
ECIR
2010
Springer

Learning to Distribute Queries into Web Search Nodes

12 years 2 months ago
Learning to Distribute Queries into Web Search Nodes
Web search engines are composed of a large set of search nodes and a broker machine that feeds them with queries. A location cache keeps minimal information in the broker to register the search nodes capable of producing the top-N results for frequent queries. In this paper we show that it is possible to use the location cache as a training dataset for a standard machine learning algorithm and build a predictive model of the search nodes expected to produce the best approximated results for queries. This can be used to prevent the broker from sending queries to all search nodes under situations of sudden peaks in query traffic and, as a result, avoid search node saturation. This paper proposes a logistic regression model to quickly predict the most pertinent search nodes for a given query.
Marcelo Mendoza, Mauricio Marín, Flavio Fer
Added 06 Dec 2010
Updated 06 Dec 2010
Type Conference
Year 2010
Where ECIR
Authors Marcelo Mendoza, Mauricio Marín, Flavio Ferrarotti, Barbara Poblete
Comments (0)
books