We consider the problem of learning to rank relevant and novel documents so as to directly maximize a performance metric called Expected Global Utility (EGU), which has several de...
Probabilistic latent semantic indexing (PLSI) represents documents of a collection as mixture proportions of latent topics, which are learned from the collection by an expectation...
Alexander Hinneburg, Hans-Henning Gabriel, Andr&eg...
The University College London Information Retrieval Group participated in both the Expert Search and Document Search tasks in the TREC2008 Enterprise Track. We used a generic two-...
: We describe our participation in the TREC 2004 Web and Terabyte tracks. For the web track, we employ mixture language models based on document full-text, incoming anchortext, and...
: The Web is huge, unstructured and diverse in quality, which makes searching for information difficult. In practice, few of the documents returned by a search engine are valuable ...