Measures of semantic similarity and relatedness in the biomedical domain

Rubenstein, 1965, Contextual correlates of synonymy, Communications of the ACM, 8, 627, 10.1145/365628.365657

Miller, 1991, Contextual correlates of semantic similarity, Language and Cognitive Processes, 6, 1, 10.1080/01690969108406936

Resnik P. Using information content to evaluate semantic similarity in a taxonomy. In: Proceedings of the 14th international joint conference on artificial intelligence. Montreal, Canada; 1995. p. 448–53.

Lin, 1998, An information-theoretic definition of similarity

Jiang J, Conrath D. Semantic similarity based on corpus statistics and lexical taxonomy. In: Proceedings of the 10th international conference on research in computational linguistics, Taipei, Taiwan; 1997. p. 19–33.

Patwardhan S, Pedersen T. Using WordNet-based context vectors to estimate the semantic relatedness of concepts. In: Proceedings of the EACL 2006 workshop, making sense of sense: Bringing computational linguistics and psycholinguistics together. Trento, Italy; 2006. p. 1–8.

Rosario B, Hearst M. Classifying semantic relations in bioscience texts. In: Proceedings of the 42nd annual meeting of the association for computational linguistics. Barcelona, Spain; 2004. p. 430–7.

Budanitsky A, Hirst G. Semantic distance in WordNet: an experimental application oriented evaluation of five measures. In: Proceedings of the NACCL 2001 Workshop: on WordNet and other lexical resources: Applications, extensions, and customizations. Pittsburgh, PA; 2001. p. 29–34.

Resnik, 1998, WordNet and class-based probabilities, 239

Patwardhan S, Banerjee S, Pedersen T. Using measures of semantic relatedness for word sense disambiguation. In: Proceedings of the fourth international conference on intelligent text processing and computational linguistics. Mexico City, Mexico; 2003. p. 241–57.

McCarthy D, Keoling R, Weeds J, Carroll J. Finding predominant word senses in untagged text. In: Proceedings of the 42nd meeting of the association for computational linguistics. Barcelona, Spain; 2004. p. 276–86.

1998

Rada R, Mili H, Bicknell E, Blettner M. Development and application of a metric on semantic nets. In: IEEE transactions on systems, man and cybernetics, 1989;19(1): p. 17–30.

Caviedes, 2004, Towards the development of a conceptual distance metric for the UMLS, J Biomed Informatics, 37, 77, 10.1016/j.jbi.2004.02.001

Lord, 2003, Investigating semantic similarity measures across the gene ontology: the relationship between sequence and annotation, Bioinformatics, 19, 1275, 10.1093/bioinformatics/btg153

The Gene Ontology Consortium, Gene Ontology: Tool for the Unification of Biology. Nat Genet 2000;25:25–9.

Wilbur, 1996, An analysis of statistical term strength and its use in the indexing and retrieval of molecular biology texts, Comput Biol Med, 26, 209, 10.1016/0010-4825(95)00055-0

Spasic I, Ananiadou S. A flexible measure of contextual similarity for biomedical terms, Pacific Biocomputing Symposium 2005;10:197–208.

Levenshtein, 1966, Binary codes capable of correcting deletions, insertions and reversals, Sov Phys Dokl, 10, 707

Schütze, 1998, Automatic word sense discrimination, Comput Linguist, 24, 97

Deerwester, 1990, Indexing by latent semantic analysis, J Am Soc Inf Sci, 41, 391, 10.1002/(SICI)1097-4571(199009)41:6<391::AID-ASI1>3.0.CO;2-9

Chute C. Classification and retrieval of patient records using natural language: an experimental application of latent semantic analysis. In: Proceedings of the annual international conference of the IEEE engineering in medicine and biology society. Orlando, FL; 1991. p. 1162–3.

Chute C, Yang Y. An evaluation of concept-based latent semantic indexing for clinical information retrieval. In: Proceedings of the 16th annual symposium on computer applications in medical care. Baltimore, MD; 1992. p. 639–43.

Chute C. The classification of medical events using latent semantic analysis. In: Advances in classification research vol. 2: Proceedings of the second ASIS SIG/CR workshop on classification research. Medford, NJ; 1992. p. 45–51.

Chute C, Yang Y, Evans D. Latent semantic indexing of medical diagnoses using UMLS semantic structures. In: Proceedings of the 15th annual symposium on computer applications in medical care. New York City, NY; 1991. p. 185–9.

Evans D, Chute C, Handerson S, Yang Y, Monardch I, Hersh W. Latent semantics as a basis for managing variation in medical terminologies. In: Proceedings of the seventh world congress on medical informatics (MEDINFO ’92). Geneva, Switzerland; 1992. p. 1462–8.

Banerjee S, Pedersen T. An adapted Lesk algorithm for word sense disambiguation using WordNet. In: Proceedings of the third international conference on intelligent text processing and computational linguistics. Mexico City, Mexico; 2002. p. 136–45.

Stevenson M, Greenwood M. A semantic approach to IE pattern induction. In: Proceedings of the 43rd annual meeting of the association for computational linguistics. Ann Arbor, MI; 2005. p. 379–86.

Raina R, Ng A, Manning C. Robust textual inference via learning and abductive reasoning. In: Proceedings of the Twentieth national conference on artificial intelligence. Pittsburgh, PA; 2005. p. 1099–105.

Burgun A, Bodenreider O. Comparing terms, concepts and semantic classes in WordNet and the Unified Medical Language System. In: Proceedings of the NAACL 2001 Workshop: WordNet and other lexical resources: Applications, extensions and customizations. Pittsburgh, PA; 2001. p. 77–82.

SNOMED-CT: Fact sheet. 2004. College of American Pathologists.

Pakhomov S. Modeling filled pauses in medical dictations. In: Proceedings of the 37th annual meeting of the association for computational linguistics. College Park, MD; 1999. p. 619–24.

Carnine, 1984, Utilization of contextual information in determining the meaning of unfamiliar words, Read Res Quart, 19, 188, 10.2307/747362

McDonald S, Ramscar M. Testing the distributional hypothesis: the influence of context on judgements of semantic similarity. In: Proceedings of the 23rd annual conference of the cognitive science society. Edinburgh, Scotland; 2001. p. 611–6.

Wu Z, Palmer M. Verb semantics and lexical selection. In: Proceedings of the 32nd annual meeting of the association for computational linguistics. Las Cruces, NM; 1994. p. 133–8.

Leacock, 1998, Combining local context and WordNet similarity for word sense identification, 265

Hirst, 1998, Lexical chains as representations of context for the detection and correction of malapropisms, 305

Patwardhan, S. Incorporating dictionary and corpus information into a context vector measure of semantic relatedness. Master of Science Thesis, Duluth, MN: Department of Computer Science. Duluth: University of Minnesota; 2003.