Word association norms, mutual information, and lexicography
Computational Linguistics
An Algorithm that Learns What‘s in a Name
Machine Learning - Special issue on natural language learning
Retrieving descriptive phrases from large amounts of free text
Proceedings of the ninth international conference on Information and knowledge management
Biterm language models for document retrieval
SIGIR '02 Proceedings of the 25th annual international ACM SIGIR conference on Research and development in information retrieval
Discovery of inference rules for question-answering
Natural Language Engineering
An empirical study of smoothing techniques for language modeling
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A study of smoothing methods for language models applied to information retrieval
ACM Transactions on Information Systems (TOIS)
Understanding user goals in web search
Proceedings of the 13th international conference on World Wide Web
Large scale testing of a descriptive phrase finder
HLT '01 Proceedings of the first international conference on Human language technology research
Evaluating answers to definition questions
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
Probabilistic model for definitional question answering
SIGIR '06 Proceedings of the 29th annual international ACM SIGIR conference on Research and development in information retrieval
Reranking answers for definitional QA using language modeling
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
A shortest path dependency kernel for relation extraction
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Will pyramids built of nuggets topple over?
HLT-NAACL '06 Proceedings of the main conference on Human Language Technology Conference of the North American Chapter of the Association of Computational Linguistics
Soft pattern matching models for definitional question answering
ACM Transactions on Information Systems (TOIS)
Introduction to Information Retrieval
Introduction to Information Retrieval
A Little Known Fact Is ... Answering Other Questions Using Interest-Markers
CICLing '07 Proceedings of the 8th International Conference on Computational Linguistics and Intelligent Text Processing
Answering definition questions using web knowledge bases
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
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Question–answering systems make good use of knowledge bases (KBs, e.g., Wikipedia) for responding to definition queries. Typically, systems extract relevant facts from articles regarding the question across KBs, and then they are projected into the candidate answers. However, studies have shown that the performance of this kind of method suddenly drops, whenever KBs supply narrow coverage. This work describes a new approach to deal with this problem by constructing context models for scoring candidate answers, which are, more precisely, statistical n-gram language models inferred from lexicalized dependency paths extracted from Wikipedia abstracts. Unlike state-of-the-art approaches, context models are created by capturing the semantics of candidate answers (e.g., “novel,”“singer,”“coach,” and “city”). This work is extended by investigating the impact on context models of extra linguistic knowledge such as part-of-speech tagging and named-entity recognition. Results showed the effectiveness of context models as n-gram lexicalized dependency paths and promising context indicators for the presence of definitions in natural language texts. © 2012 Wiley Periodicals, Inc.