SIGIR'98 papers: A Method for Scoring Correlated Features in Query
Expansion
A Method for Scoring Correlated Features in Query Expansion
Martin Franz
IBM T. J. Watson Research Center,
P.O.B. 718, Yorktown Heights, NY 10598, U.S.A.
Salim Roukos
IBM T. J. Watson Research Center,
P.O.B. 718, Yorktown Heights, NY 10598, U.S.A.
Abstract
In this poster we describe experiments in information retrieval using a new method for scoring correlated features. This method
uses information about word co-occurrences in the documents ranking high after the initial scoring to reduce combined scores of
correlated words. We have experimented with this technique in conjunction with both simple Okapi scoring and a query expansion
method using a probabilistic model, improving system performance in the context of TREC standardized tasks.