A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2011; you can also visit the original URL.
The file type is application/pdf
.
Random walk term weighting for information retrieval
2007
Proceedings of the 30th annual international ACM SIGIR conference on Research and development in information retrieval - SIGIR '07
We present a way of estimating term weights for Information Retrieval (IR), using term co-occurrence as a measure of dependency between terms. We use the random walk graphbased ranking algorithm on a graph that encodes terms and co-occurrence dependencies in text, from which we derive term weights that represent a quantification of how a term contributes to its context. Evaluation on two TREC collections and 350 topics shows that the random walk-based term weights perform at least comparably to
doi:10.1145/1277741.1277930
dblp:conf/sigir/BlancoL07
fatcat:5uolqrtyane27dw6lpoemf25ra