The ranking function used by search engines to order results is learned from labeled training data. Each training point is a (query, URL) pair that is labeled by a human judge who...
Rakesh Agrawal, Alan Halverson, Krishnaram Kenthap...
Interactive image search or relevance feedback is the process which helps a user refining his query and finding difficult target categories. This consists in a step-by-step lab...
Hichem Sahbi, Patrick Etyngier, Jean-Yves Audibert...
In some retrieval situations, a system must search across multiple collections. This task, referred to as federated search, occurs for example when searching a distributed index o...
Determining the user intent of Web searches is a difficult problem due to the sparse data available concerning the searcher. In this paper, we examine a method to determine the us...
Bernard J. Jansen, Danielle L. Booth, Amanda Spink
We propose mixtures of hidden Markov models for modelling clickstreams of web surfers. Hence, the page categorization is learned from the data without the need for a (possibly cumb...