Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Empirical methods for artificial intelligence
Empirical methods for artificial intelligence
Assessing agreement on classification tasks: the kappa statistic
Computational Linguistics
Message classification in the call center
ANLC '00 Proceedings of the sixth conference on Applied natural language processing
A non-projective dependency parser
ANLC '97 Proceedings of the fifth conference on Applied natural language processing
An approach for adding noise-tolerance to restricted-domain information retrieval
NLDB'10 Proceedings of the Natural language processing and information systems, and 15th international conference on Applications of natural language to information systems
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We present a question answering system that can handle noisy and incomplete natural language data, and methods and measures for the evaluation of question answering systems. Our question answering system is based on the vector space model and linguistic analysis of the natural language data. In the evaluation procedure, we test eight different preprocessing schemes for the data, and come to the conclusion that lemmatization combined with breaking compound words into their constituents gives significantly better results than the baseline. The evaluation process is based on stratified random sampling and bootstrapping. To measure the correctness of an answer, we use partial credits as well as full credits.