Date of Original Version

11-2010

Type

Conference Proceeding

Journal Title

The Nineteenth Text REtrieval Conference (TREC 2010) Proceedings

Volume

SP 500-294

Abstract or Description

In this paper we describe Carnegie Mellon University’s submission to the TREC 2010 Web Track. Our baseline run combines different methods, of which in particular the spam prior and mixture model were found the most effective. We also experimented with expansion over the Wikipedia corpus and found that picking the right Wikipedia articles for expansion can improve performance substantially. Furthermore, we did preliminary experiments with combining expansion over the Wikipedia corpus with expansion over the top ranked web pages

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Published In

The Nineteenth Text REtrieval Conference (TREC 2010) Proceedings, SP 500-294.