A language modeling approach to information retrieval
Proceedings of the 21st annual international ACM SIGIR conference on Research and development in information retrieval
High performance question/answering
Proceedings of the 24th annual international ACM SIGIR conference on Research and development in information retrieval
QuASM: a system for question answering using semi-structured data
Proceedings of the 2nd ACM/IEEE-CS joint conference on Digital libraries
Faceted metadata for image search and browsing
Proceedings of the SIGCHI Conference on Human Factors in Computing Systems
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
COLING '02 Proceedings of the 19th international conference on Computational linguistics - Volume 1
Question classification with log-linear models
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
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In this paper we present a novel multiple-taxonomy question classification system, facing the challenge of assigning categories inmultiple taxonomies to natural language questions. We applied our system to category search on faceted information. The system provides a natural language interface to faceted information, detecting the categories requested by the user and narrowing down the document search space to those documents pertaining to the facet values identified. The system was developed in the framework of language modeling, and the models to detect categories are inferred directly from the corpus of documents.