Word association norms, mutual information, and lexicography
Computational Linguistics
CYC: a large-scale investment in knowledge infrastructure
Communications of the ACM
WordNet: a lexical database for English
Communications of the ACM
Unsupervised learning of soft patterns for generating definitions from online news
Proceedings of the 13th international conference on World Wide Web
Logic form transformation of WordNet and its applicability to question answering
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Question answering using constraint satisfaction: QA-by-Dossier-with-Constraints
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Improving QA accuracy by question inversion
ACL-44 Proceedings of the 21st International Conference on Computational Linguistics and the 44th annual meeting of the Association for Computational Linguistics
An exploration of the principles underlying redundancy-based factoid question answering
ACM Transactions on Information Systems (TOIS)
Using information content to evaluate semantic similarity in a taxonomy
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 1
Numerical data integration for cooperative question-answering
KRAQ '06 Proceedings of the Workshop KRAQ'06 on Knowledge and Reasoning for Language Processing
Measuring semantic similarity by latent relational analysis
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
Open-domain question: answering
Foundations and Trends in Information Retrieval
Learning to rank for quantity consensus queries
Proceedings of the 32nd international ACM SIGIR conference on Research and development in information retrieval
Robust similarity measures for named entities matching
COLING '08 Proceedings of the 22nd International Conference on Computational Linguistics - Volume 1
Information Processing and Management: an International Journal
Identifying functional relations in web text
EMNLP '10 Proceedings of the 2010 Conference on Empirical Methods in Natural Language Processing
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We present in this paper Type Nanotheories (TN), a framework for representing the knowledge necessary for performing similarity comparisons between pairs of terms of the same type. TN itself uses another methodology, namely Support Outcomes, which is also introduced. Many IR and NLP applications use redundancy as a factor to increase confidence, and TN-based comparisons can determine redundancy better than simple string comparisons. Results include a showing of a 14% increase in Confidence-Weighted Score for an end-to-end QA system and an up to 68% improvement over baseline in an answer-key equivalencing experiment.