Mining the Web for Synonyms: PMI-IR versus LSA on TOEFL (original) (raw)

References

1. Church, K.W., Hanks, P.: Word Association Norms, Mutual Information and Lexicography. In: Proceedings of the 27th Annual Conference of the Association of Computational Linguistics, (1989) 76–83.
   Google Scholar
2. Church, K.W., Gale, W., Hanks, P., Hindle, D.: Using Statistics in Lexical Analysis. In: Uri Zernik (ed.), Lexical Acquisition: Exploiting On-Line Resources to Build a Lexicon. New Jersey: Lawrence Erlbaum (1991) 115–164.
   Google Scholar
3. Alta Vista, Alta Vista Company, Palo Alto, California, http://www.altavista.com/.
4. Test of English as a Foreign Language (TOEFL), Educational Testing Service, Princeton, New Jersey, http://www.ets.org/.
5. Tatsuki, D.: Basic 2000 Words-Synonym Match 1. In: Interactive JavaScript Quizzes for ESL Students, http://www.aitech.ac.jp/~iteslj/quizzes/js/dt/mc-2000-01syn.html (1998).
6. Landauer, T.K., Dumais, S.T.: A Solution to Plato’s Problem: The Latent Semantic Analysis Theory of the Acquisition, Induction, and Representation of Knowledge. Psychological Review, 104 (1997) 211–240.
   Article Google Scholar
7. Deerwester, S., Dumais, S.T., Furnas, G.W., Landauer, T.K., Harshman, R.: Indexing by Latent Semantic Analysis. Journal of the American Society for Information Science, 41 (1990) 391–407.
   Article Google Scholar
8. Berry, M.W., Dumais, S.T., Letsche, T.A.: Computational Methods for Intelligent Information Access. Proceedings of Supercomputing’ 95, San Diego, California, (1995).
   Google Scholar
9. Manning, C.D., Schütze, H.: Foundations of Statistical Natural Language Processing. Cambridge, Massachusetts: MIT Press (1999).
   MATH Google Scholar
10. Firth, J.R.: A Synopsis of Linguistic Theory 1930–1955. In Studies in Linguistic Analysis, pp. 1–32. Oxford: Philological Society (1957). Reprinted in F.R. Palmer (ed.), Selected Papers of J.R. Firth 1952–1959, London: Longman (1968).
    Google Scholar
11. Alta Vista: Alta Vista Advanced Search Cheat Sheet, Alta Vista Company, Palo Alto, California, http://doc.altavista.com/adv_search/syntax.html (2001).
12. Fellbaum, C. (ed.): WordNet: An Electronic Lexical Database. Cambridge, Massachusetts: MIT Press (1998). For more information: http://www.cogsci.princeton.edu/~wn/.
    MATH Google Scholar
13. Haase, K.: Interlingual BRICO. IBM Systems Journal, 39 (2000) 589–596. For more information: http://www.framerd.org/brico/.
    Article Google Scholar
14. Vossen, P. (ed.): EuroWordNet: A Multilingual Database with Lexical Semantic Networks. Dordrecht, Netherlands: Kluwer (1998). See: http://www.hum.uva.nl/~ewn/.
    MATH Google Scholar
15. Turney, P.D.: Learning Algorithms for Keyphrase Extraction. Information Retrieval, 2 (2000) 303–336.
    Article Google Scholar
16. Grefenstette, G.: Finding Semantic Similarity in Raw Text: The Deese Antonyms. In: R. Goldman, P. Norvig, E. Charniak and B. Gale (eds.), Working Notes of the AAAI Fall Symposium on Probabilistic Approaches to Natural Language. AAAI Press (1992) 61–65.
    Google Scholar
17. Schütze, H.: Word Space. In: S.J. Hanson, J.D. Cowan, and C.L. Giles (eds.), Advances in Neural Information Processing Systems 5, San Mateo California: Morgan Kaufmann (1993) 895–902.
    Google Scholar
18. Lin, D.: Automatic Retrieval and Clustering of Similar Words. In: Proceedings of the 17th International Conference on Computational Linguistics and 36th Annual Meeting of the Association for Computational Linguistics, Montreal (1998) 768–773.
    Google Scholar
19. Richardson, R., Smeaton, A., Murphy, J.: Using WordNet as a Knowledge Base for Measuring Semantic Similarity between Words. In Proceedings of AICS Conference. Trinity College, Dublin (1994).
    Google Scholar
20. Lee, J.H., Kim, M.H., Lee, Y.J.: Information Retrieval Based on Conceptual Distance in IS-A Hierarchies. Journal of Documentation, 49 (1993) 188–207.
    Article Google Scholar
21. Resnik, P.: Semantic Similarity in a Taxonomy: An Information-Based Measure and its Application to Problems of Ambiguity in Natural Language. Journal of Artificial Intelligence Research, 11 (1998) 95–130.
    Google Scholar
22. Jiang, J., Conrath, D.: Semantic Similarity Based on Corpus Statistics and Lexical Taxonomy. In: Proceedings of the 10th International Conference on Research on Computational Linguistics, Taiwan, (1997).
    Google Scholar
23. Brin, S., Motwani, R., Ullman, J., Tsur, S.: Dynamic Itemset Counting and Implication Rules for Market Basket Data. In: Proceedings of the 1997 ACM-SIGMOD International Conference on the Management of Data (1997) 255–264.
    Google Scholar
24. Sullivan, D.: Search Engine Sizes. SearchEngineWatch.com, internet.com Corporation, Darien, Connecticut, http://searchenginewatch.com/reports/sizes.html (2000).
    Google Scholar
25. Papadimitriou, C.H., Raghavan, P., Tamaki, H., Vempala, S.: Latent Semantic Indexing: A Probabilistic Analysis. In: Proceedings of the Seventeenth ACM-SIGACT-SIGMOD-SIGART Symposium on Principles of Database Systems, Seattle, Washington (1998) 159–168.
    Google Scholar
26. Sparck Jones, K.: Comparison Between TREC2 and TREC3. In: D. Harman (ed.), The Third Text REtrieval Conference (TREC3), National Institute of Standards and Technology Special Publication 500–226, Gaithersburg, Maryland (1994) C1–C4.
    Google Scholar
27. Buckley, C., Salton, G., Allan, J., Singhal, A.: Automatic Query Expansion Using SMART: TREC 3. In: The Third Text REtrieval Conference (TREC3), D. Harman (ed.), National Institute of Standards and Technology Special Publication 500–226, Gaithersburg, Maryland (1994) 69–80.
    Google Scholar

Download references