Identyfikatory
Warianty tytułu
Języki publikacji
Abstrakty
There is a renewed interest in word sense disambiguation (WSD) as it contributes to various applications in natural language processing. In this paper we survey vector-based methods for WSD in machine learning. All the methods are corpus-based and use definition of context in the sense introduced by S. Marcus [11].
Słowa kluczowe
Wydawca
Czasopismo
Rocznik
Tom
Strony
433--442
Opis fizyczny
Bibliogr. 19 poz.
Twórcy
autor
- Faculty of Mathematics and Computer Science, University Babes-Bolyai, Str. Kogalniceanu nr 1, Cluj-Napoca, Romania, dtatar@cs.ubbcluj.ro
Bibliografia
- [1] C. Brun, A client/server architecture for word sense disambiguation,cites.ist.psu.edu/article/brun00clientserver.htlm.
- [2] I. Dagan, L. Lee, F. Pereira, Similarity-based models of word cooccurrences probabilities, MLJ, 34(1-3), 1999.
- [3] W. Daelemans, Machine Learning Approach in Syntactic Wordclass Tagging, Kluwer Academic Publishers, pp 285–304, 1999.
- [4] C. Fellbaum, ed., WordNet An Electronic Lexical Database, The MIT Press, 1998.
- [5] S. Gauch, J. Wang, S.M. Rachakonda, A corpus analysis approach for automatic query expansion and its extension to multiple databases, CIKM’97- Information and Knowledge management, 1997.
- [6] N. Ide, J. Veronis, Introduction to the special issue on WSD: the state of the art, Computational Linguistics, 24(1) 1998, 1–40.
- [7] D. Jurafsky, J. Martin, Speech and Language Processing, Prentice Hall, 2000.
- [8] A. Kilgarriff, What is WSD Good for?, ITRI Technical Report Series, August, 1997.
- [9] D. Lin, Automatic retrieval and clustering of similar words, COLING-ACL’98, Montreal, 1998.
- [10] C. Manning, H. Schutze, Foundation of Statistical Natural Language Processing, MIT, 1999.
- [11] S. Marcus, Lingvistica matematic˘a, Ed. Didactic˘a si Pedagogic˘a, Bucures¸ti, 1966.
- [12] P. Resnik, D. Yarowsky,Distinguishing Systems and Distinguishing sense: new evaluation methods forWSD, Natural Language Engineering, 1, nr 1, 1998.
- [13] M. Sahlgren, Vector-based semantic analysis: representing word meanings based on random labels, in The Acquisition and Representation of Word Meaning, Kluwer Academic Publishers, 2001.
- [14] H. Schutze, Automatic word sense discrimination, Computational Linguistics, 24(1) 1998, 97–123.
- [15] G. Serban, D. Tatar, UBB system at Senseval3, Proceedings of Workshop in Word Disambiguation, ACL 2004, Barcelona, July 2004, pp 226–229.
- [16] D. Tatar, G. Serban, A new algorithm for WSD, Studia Univ. Babes-Bolyai, Informatica, 2001, nr.2, 99–108.
- [17] D. Tatar, Inteligenţă artificială: demonstrare automată de teoreme, prelucrarea limbajului natural, Editura Albastra, Microinformatica, 2001.
- [18] D. Widdows, A mathematical model for context and word meaning, Fourth International Conference on Modeling and using context, Stanford, California, June 23-25, 2003.
- [19] D. Yarowsky, Hierarchical Decision Lists for WSD, Kluwer Acadmic Publishers, 1999
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-article-BUS2-0005-0142