Classifying search engine queries using the web as background knowledge Export

@article{sigkdd2005:background, abstract = {The performance of search engines crucially depends on their ability to capture the meaning of a query most likely intended by the user. We study the problem of mapping a search engine query to those nodes of a given subject taxonomy that characterize its most likely meanings. We describe the architecture of a classification system that uses a web directory to identify the subject 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.}, address = {New York, NY, USA}, author = {Vogel, David and Bickel, Steffen and Haider, Peter and Schimpfky, Rolf and Siemen, Peter and Bridges, Steve and Scheffer, Tobias}, citeulike-article-id = {3433261}, citeulike-linkout-0 = {http://portal.acm.org/citation.cfm?id=1117469}, citeulike-linkout-1 = {http://dx.doi.org/10.1145/1117454.1117469}, doi = {10.1145/1117454.1117469}, issn = {1931-0145}, journal = {SIGKDD Explor. Newsl.}, keywords = {2005, categorization, cup, kdd, query}, number = {2}, pages = {117--122}, posted-at = {2008-10-21 12:16:33}, priority = {2}, publisher = {ACM}, title = {Classifying search engine queries using the web as background knowledge}, url = {http://dx.doi.org/10.1145/1117454.1117469}, volume = {7}, year = {2005} }

TY - JOUR ID - sigkdd2005:background L3 - citeulike-article-id:3433261 N2 - The performance of search engines crucially depends on their ability to capture the meaning of a query most likely intended by the user. We study the problem of mapping a search engine query to those nodes of a given subject taxonomy that characterize its most likely meanings. We describe the architecture of a classification system that uses a web directory to identify the subject 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. IS - 2 JF - SIGKDD Explor. Newsl. SN - 1931-0145 AD - New York, NY, USA EP - 122 TI - Classifying search engine queries using the web as background knowledge PB - ACM VL - 7 SP - 117 KW - 2005 KW - categorization KW - cup KW - kdd KW - query AU - Vogel, David AU - Bickel, Steffen AU - Haider, Peter AU - Schimpfky, Rolf AU - Siemen, Peter AU - Bridges, Steve AU - Scheffer, Tobias PY - 2005/// UR - http://dx.doi.org/10.1145/1117454.1117469 ER -