Classifying Search Engine Queries Using the Web as Background Knowledge David Vogel, Steffen Bickel, Peter Haider, Rolf Schimpfky, Peter Siemen, Steve Bridges, and Tobias Scheffer   View Paper (PDF)   Return to December 2005, Volume 7, Issue 2 Abstract The performance of search engines crucially depends on their ability to capture the meaning of a query most likely in- tended by the user. We study the problem of mapping a search engine query to those nodes of a given sub ject tax- onomy that characterize its most likely meanings. We de- scribe the architecture of a classification system that uses a web directory to identify the sub ject context that the query terms are frequently used in. Based on its performance on the classification of 800,000 example queries recorded from MSN search, the system received the Runner-Up Award for Query Categorization Performance of the KDD Cup 2005. ©2006 Association for Computing Machinery