Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Passage-level evidence in document retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Pivoted document length normalization
SIGIR '96 Proceedings of the 19th annual international ACM SIGIR conference on Research and development in information retrieval
Proceedings of the 20th annual international ACM SIGIR conference on Research and development in information retrieval
Probabilistic models of information retrieval based on measuring the divergence from randomness
ACM Transactions on Information Systems (TOIS)
A maximum entropy approach to named entity recognition
A maximum entropy approach to named entity recognition
Improving question answering using named entity recognition
NLDB'05 Proceedings of the 10th international conference on Natural Language Processing and Information Systems
Formal Grammar for Hispanic Named Entities Analysis
CICLing '09 Proceedings of the 10th International Conference on Computational Linguistics and Intelligent Text Processing
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In a previous paper we proved that Named Entity Recognition plays an important role to improve Question Answering by both increasing the quality of the data and by reducing its quantity. Here we present a more in-depth discussion, studying several ways in which NER can be applied in order to produce a maximum data reduction. We achieve a 60% reduction without significant data loss and a 92.5% with a reasonable implication in data quality.