Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language

Journal of Artificial Intelligence Research

Volumn 11, Issue , 1999, Pages 95-130

  Resnik, Philip ^a  

^a UNIVERSITY OF MARYLAND   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

EID: 0002016474     PISSN: 10769757     EISSN: None     Source Type: Journal    
DOI: 10.1613/jair.514     Document Type: Article

References (72)

1. Agarwal, R., & Boggess, L. (1992). A simple but useful approach to conjunct identification. In Proceedings of the 30th Annual Meeting of the Association for Computational Linguistics, pp. 15-21. Association for Computational Linguistics.
2. Bensch, P. A., & Savitch, W. J. (1992). An occurrence-based model of word categorization. Presented at 3rd Meeting on Mathematics of Language (MOL3).
3. Brill, E. (1991). Discovering the lexical features of a language. In Proceedings of the 29th Annual Meeting of the Association for Computational Linguistics, Berkeley, CA.
4. Brill, E., & Resnik, P. (1994). A rule-based approach to prepositional phrase attachment disambiguation. In Proceedings of the 15th International Conference on Computational Linguistics (COLING-94).
5. Brown, P. F., Delia Pietra, V. J., deSouza, P. V., Lai, J. C., & Mercer, R. L. (1992). Class-based n-gram models of natural language. Computational Linguistics, 18(4), 467-480.
6. CETA (1982). Chinese Dictionaries: an Extensive Bibliography of Dictionaries in Chinese and Other Languages. Chinese-English Translation Assistance Group, Greenwood Publishing.
7. Church, K. W., & Mercer, R. (1993). Introduction to the special issue on computational linguistics using large corpora. Computational Linguistics, 19(1), 1-24.
8. Church, K. W., & Patil, R. (1982). Coping with syntactic ambiguity or how to put the block in the box on the table. American Journal of Computational Linguistics, 8(3-4), 139-149.
9. Collins, A., & Loftus, E. (1975). A spreading activation theory of semantic processing. Psychological Review, 82, 407-428.
10. Collins, M., & Brooks, J. (1995). Prepositional phrase attachment through a backed-off model. In Third Workshop on Very Large Corpora. Association for Computational Linguistics, cmp-lg/9506021.
11. Cowie, J., Guthrie, J., & Guthrie, L. (1992). Lexical disambiguation using simulated annealing. In Proceedings of the 14th International Conference on Computational Linguistics (COLING-92), pp. 359-365 Nantes, France.
12. Digital Equipment Corporation (1998). AltaVista web page: Refine, or cow9?.. http://altavista.digital.com/av/content/about_our_technology_cow9.htm.
13. Dorr, B. J. (1997). Large-Scale Dictionary Construction for Foreign Language Tutoring and Interlingual Machine Translation. Machine Translation, 12(4), 271-322.
14. Fellbaum, C. (Ed.). (1998). WordNet: An Electronic Lexical Database. MIT Press.
15. Francis, W. N., & Kučera, H. (1982). Frequency Analysis of English Usage: Lexicon and Grammar. Houghton Mifflin, Boston.
16. Goldstone, R. L. (1999). Similarity. In MIT Encyclopedia of the Cognitive Sciences. MIT Press, Cambridge, MA.
17. Grefenstette, G. (1992). Use of syntactic context to produce term association lists for text retrieval. In Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 89-97.
18. Grefenstette, G. (1994). Explorations in Automatic Thesaurus Discovery. Kluwer, Boston.
19. Harman, D. (1992). Relevance feedback revisited. In Proceedings of the Fifteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 1-10.
20. Hearst, M. (1991). Noun homograph disambiguation using local context in large corpora. In Proceedings of the 7th Annual Conference of the University of Waterloo Centre for the New OED and Text Research Oxford.
21. Hindle, D., & Rooth, M. (1993). Structural ambiguity and lexical relations. Computational Linguistics, 19(1), 103-120.
22. Ji, D., Gong, J., & Huang, C. (1998). Combining a Chinese thesaurus with a Chinese dictionary. In COLING-ACL '98, pp. 600-606. Université de Montreal.
23. Katz, S. M. (1987). Estimation of probabilities from sparse data for the language model component of a speech recognizer. IEEE Transactions on Acoustics, Speech and Signal Processing, ASSP-35(3), 400-401.
24. Khinchin, A. I. (1957). Mathematical Foundations of Information Theory. New York: Dover Publications. Translated by R. A. Silverman and M. D. Friedman.
25. Klavans, J. L., & Tzoukermann, E. (1995). Dictionaries and Corpora: Combining Corpus and Machine-Readable Dictionary Data for Building Bilingual Lexicons. Machine Translation, 10, 185-218.
26. Kobayasi, Y., Takunaga, T., & Tanaka, H. (1994). Analysis of Japanese compound nouns using collocational information. In Proceedings of the 15th International Conference on Computational Linguistics (COLING-94).
27. Krovetz, R., & Croft, W. B. (1992). Lexical ambiguity and information retrieval. ACM Transactions on Information Systems, 10(2), 115-141.
28. Kurohashi, S., & Nagao, M. (1992). Dynamic programming method for analyzing conjunctive structures in Japanese. In Proceedings of the 14th International Conference on Computational Linguistics (COLING-92) Nantes, France.
29. Lauer, M. (1994). Conceptual association for compound noun analysis. In Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics Las Cruces, New Mexico. Student Session.
30. Lauer, M. (1995). Designing Statistical Language Learners: Experiments on Noun Compounds. Ph.D. thesis, Macquarie University, Sydney, Australia.
31. Leacock, C., & Chodorow, M. (1994). Filling in a sparse training space for word sense identification. ms.
32. Lee, J. H., Kim, M. H., & Lee, Y. J. (1993). Information retrieval based on conceptual distance in IS-A hierarchies. Journal of Documentation, 49(2), 188-207.
33. Lee, L. (1997). Similarity-based approaches to natural language processing. Tech. rep. TR-11-97, Harvard University. Doctoral dissertation, cmp-lg/9708011.
34. Lesk, M. (1986). Automatic sense disambiguation using machine readable dictionaries: how to tell a pine cone from an ice cream cone. In Proceedings of the 1986 SIGDOC Conference, pp. 24-26.
35. Li, H., & Abe, N. (1995). Generalizing case frames using a thesaurus and the MDL principle. In Proceedings of the International Conference on Recent Advances in NLP Velingrad, Bulgaria.
36. Lin, D. (1997). Using syntactic dependency as local context to resolve word sense ambiguity. In Proceedings of the 35th Annual Meeting of the Association for Computational Linguistics and 8th Conference of the European Chapter of the Association for Computational Linguistics Madrid, Spain.
37. Lin, D. (1998). An information-theoretic definition of similarity. In Proceedings of the Fifteenth International Conference on Machine Learning (ICML-98) Madison, Wisconsin.
38. Marcus, M. P., Santorini, B., & Marcinkiewicz, M. (1993). Building a large annotated corpus of English: the Penn Treebank. Computational Linguistics, 19, 313-330.
39. McKeown, K., & Hatzivassiloglou, V. (1993). Augmenting lexicons automatically: Clustering semantically related adjectives. In Bates, M. (Ed.), ARPA Workshop on Human Language Technology. Morgan Kaufmann.
40. Medin, D., Goldstone, R., & Gentner, D. (1993). Respects for similarity. Psychological Review, 100(1), 254-278.
41. Merlo, P., Crocker, M., & Berthouzoz, C. (1997). Attaching multiple prepositional phrases: Generalized backed-off estimation. In Proceedings of the Second Conference on Empirical Methods in Natural Language Processing (EMNLP-2). cmp-lg/9710005.
42. Miller, G. (1990). WordNet: An on-line lexical database. International Journal of Lexicography, 5(4). (Special Issue).
43. Miller, G. A., & Charles, W. G. (1991). Contextual correlates of semantic similarity. Language and Cognitive Processes, 6(1), 1-28.
44. Morrissey, R. (1993). Texts and contexts: The ARTFL database in French studies. Profession 93, 27-33. http://humanities.uchicago.edu/homes/publications/romoart.html.
45. Pereira, F., Tishby, N., & Lee, L. (1993). Distributional clustering of English words. In Proceedings of the 31st Annual Meeting of the Association for Computational Linguistics (ACL-93) Morristown, New Jersey. Association for Computational Linguistics.
46. Quillian, M. R. (1968). Semantic memory. In Minsky, M. (Ed.), Semantic Information Processing. MIT Press, Cambridge, MA.
47. Rada, R., & Bicknell, E. (1989). Ranking documents with a thesaurus. JASIS, 40(5), 304-310.
48. Rada, R., Mili, H., Bicknell, E., & Blettner, M. (1989). Development and application of a metric on semantic nets. IEEE Transaction on Systems, Man, and Cybernetics, 19(1), 17-30.
49. Ratnaparkhi, A., & Roukos, S. (1994). A maximum entropy model for prepositional phrase attachment. In Proceddings of the ARPA Workshop on Human Language Technology Plainsboro, NJ.
50. Resnik, P. (1993a). Selection and Information: A Class-Based Approach to Lexical Relationships. Ph.D. thesis, University of Pennsylvania. (ftp://ftp.cis.upenn.edu/pub/ircs/tr/93-42.ps.Z).
51. Resnik, P. (1993b). Semantic classes and syntactic ambiguity. In Proceedings of the 1993 ARPA Human Language Technology Workshop. Morgan Kaufmann.
52. Resnik, P. (1995). Using information content to evaluate semantic similarity in a taxonomy. In Proceedings of the 14th International Joint Conference on Artificial Intelligence (IJCAI-95). (cmp-lg/9511007).
53. Resnik, P. (1996). Selectional constraints: An information-theoretic model and its computational realization. Cognition, 61, 127-159.
54. Resnik, P. (1998a). Disambiguating noun groupings with respect to Wordnet senses. In Armstrong, S., Church, K., Isabelle, P., Tzoukermann, E., & Yarowsky, D. (Eds.), Natural Language Processing Using Very Large Corpora. Kluwer.
55. Resnik, P. (1998b). WordNet and class-based probabilities. In Fellbaum, C. (Ed.), WordNet: An Electronic Lexical Database. MIT Press.
56. Resnik, P., & Yarowsky, D. (1997). A perspective on word sense disambiguation methods and their evaluation. In ANLP Workshop on Tagging Text with Lexical Semantics Washington, D.C.
57. Resnik, P., & Yarowsky, D. (1999). Distinguishing systems and distinguishing senses: New evaluation methods for word sense disambiguation. Natural Language Engineering. (to appear).
58. Richardson, R., Smeaton, A. F., & Murphy, J. (1994). Using WordNet as a knowledge base for measuring semantic similarity between words. Working paper CA-1294, Dublin City University, School of Computer Applications, Dublin, Ireland, ftp://ftp.compapp.dcu.ie/pub/w-papers/1994/CA1294.ps.Z.
59. Ross, S. (1976). A First Course in Probability. Macmillan.
60. Rubenstein, H., & Goodenough, J. (1965). Contextual correlates of synonymy. CACM, 5(10), 627-633.
61. Salton, G. (1989). Automatic Text Processing. Addison-Wesley.
62. Schütze, H. (1993). Word space. In Hanson, S. J., Cowan, J. D., & Giles, C. L. (Eds.), Advances in Neural Information Processing Systems 5, pp. 895-902. Morgan Kaufmann Publishers, San Mateo CA.
63. Sinclair (ed.), J. (1987). Collins COBUILD English Language Dictionary. Collins: London.
64. Sussna, M. (1993). Word sense disambiguation for free-text indexing using a massive semantic network. In Proceedings of the Second International Conference on Information and Knowledge Management (CIKM-93) Arlington, Virginia.
65. Tversky, A. (1977). Features of similarity. Psychological Review, 84, 327-352.
66. Voorhees, E. M. (1993). Using WordNet to disambiguate word senses for text retrieval. In Korfhage, R., Rasmussen, E., & Willett, P. (Eds.), Proceedings of the Sixteenth Annual International ACM SIGIR Conference on Research and Development in Information Retrieval, pp. 171-180.
67. Voorhees, E. M. (1994). Query expansion using lexical-semantic relations. In 17th International Conference on Research and Development in Information Retrieval (SIGIR '94) Dublin, Ireland.
68. Vossen, P. (1998). Special issue on Euro WordNet. Computers and the Humanities, 32(2/3).
69. Weiss, S. M., & Kulikowski, C. A. (1991). Computer systems that learn: classification and prediction methods from statistics, neural nets, machine learning, and expert systems. Morgan Kaufmann, San Mateo, CA.
70. Whittemore, G., Ferrara, K., & Brunner, H. (1990). Empirical study of predictive powers of simple attachment schemes for post-modifier prepositional phrases. In Proceedings of the 28th Annual Meeting of the Association for Computational Linguistics, pp. 23-30. Pittsburgh, Pennsylvania.
71. Wilks, Y., & Stevenson, M. (1996). The grammar of sense: Is word-sense tagging much more than part-of-speech tagging?.. Technical Report CS-96-05, cmp-lg/9607028.
72. Wu, Z., & Palmer, M. (1994). Verb Semantics and Lexical Selection. In Proceedings of the 32nd Annual Meeting of the Association for Computational Linguistics Las Cruces, New Mexico.