Pseudo-relevance feedback (PRF) improves search quality by expanding the query using terms from high-ranking documents from an initial retrieval. Although PRF can often result in ...
Marc-Allen Cartright, James Allan, Victor Lavrenko...
: A fully operational large scale digital library is likely to be based on a distributed architecture and because of this it is likely that a number of independent search engines m...
We present BAYESUM (for "Bayesian summarization"), a model for sentence extraction in query-focused summarization. BAYESUM leverages the common case in which multiple do...
In document retrieval using pseudo relevance feedback, after initial ranking, a fixed number of top-ranked documents are selected as feedback to build a new expansion query model. ...
People are seldom aware that their search queries frequently mismatch a majority of the relevant documents. This may not be a big problem for topics with a large and diverse set o...