Investigação sobre a Identificação de Assuntos em Mensagens de Chat
Resumo
O objetivo do presente trabalho é investigar o processo de classificaçã o de textos sobre mensagens de um chat na Web. As mensagens de chat possuem algumas particularidades como concisão, pouco cuidado com correções ortográficas e revisões, devido a serem escritas às pressas e geralmente por pessoas leigas. Neste trabalho, foram utilizados métodos simples de classificação para investigar as particularidades do processo de classificação sobre este tipo de texto.Referências
BAKER, L. D. & McCALLUM, A. K. 1998. Distributional clustering of words for text classification. IN: Proceedings ACM International Conference on Re search and Development in Information Retrieval, SIGIR-98, 21., Melbourne, 1998. p.96-103.
GUARINO, Nicola. 1998. Formal Ontology and Information Systems. In: International Conference on Formal Ontologies in Information Systems-FOIS'98, Trento, Itália, Junho de 1998. p. 3-15
JOACHIMS, T. 1997. A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization. IN: Proceedings International Conference on Machine Learning, ICML-97, Nashville, 1997. p.143-151.
KHAN, Faisal M. ET AL. 2002. Mining chat-room conversations for social and semantic interactions. Technical Report, LU-CSE-02-011, Lehigh University.
KNIGHT, Kevin. 1999. Mining online text. Communications of the ACM, v.42, n.11, p.58-61.
LANG, K. 1995. NewsWeeder: learning to filter netnews. IN: Proceedings International Conference on Machine Learning, ICML-95, 12., Lake Tahoe, 1995. p.331-339.
LEWIS, David D. 1998. Naive (bayes) at forty: The independence assumption in information retrieval. In: European Conference on Machine Learning, Chemnitz, Alemanha, 1998. p.4-15. (Lecture Notes in Computer Science, v.1398).
LOH, S.; WIVES, L. K.; OLIVEIRA, J. P. M. 2000. Concept-based knowledge discovery in texts extracted from the Web. ACM SIGKDD Explorations, v.2, n.1, Julho de 2000, p. 29-39.
McCALLUM, A. K. & NIGAM, K. 1998. Employing EM in pool-based active learning for text classification. IN: Proceedings International Conference on Machine Learning, ICML-98, Madison, 1998. p.350-358.
McCALLUM, A. K.; ROSENFELD, R.; MITCHELL, T. M.; NG, A. Y. 1998. Improving text classification by shrinkage in a hierarchy of classes. IN: Proceedings International Conference on Machine Learning, ICML-98, Madison, 1 998. p.359-367.
NIGAM, K.; McCALLUM, A. K.; THRUN, S.; MITCHELL, T. M. 2000. Text classification from labeled and unlabeled documens using EM. Machine Learning, v. 39, n.2/3, p.103-134.
RAGAS, Hein & KOSTER, Cornelis H. A. 1998. Four text classification algorithms compared on a Dutch corpus. In: International ACM-SIGIR Conference on Research and Development in Information Retrieval, Melbourne, 1998, p.369-370.
RILOFF, Ellen & LEHNERT, Wendy. 1994. Information extraction as a basis for high-precision text classification. ACM Transactions on Information Systems, v.12, n.3, Julho de 1994, p.296-333.
ROCCHIO, J. J. 1966. Document retrieval systems-optimization and evaluation. Tese (Doutorado)-Harvard University, Cambridge.
SALTON, G. & McGILL, M. J. 1983. Introduction to modern information retrieval. New York: McGraw-Hill, 1983.
SEBASTIANI, Fabrizio. 2002. Machine learning in automated text categorization. ACM Computing Surveys, v.34, n.1, Março de 2002.
SCHAPIRE, R. E. & SINGER, Y. 2000. BoosTexter: a boosting-based system for text categorization. Machine Learning, v. 39, n.2/3, p.135-168.
SOWA, John F. 2002. Building, sharing, and merging ontologies. Disponível em [link]
GUARINO, Nicola. 1998. Formal Ontology and Information Systems. In: International Conference on Formal Ontologies in Information Systems-FOIS'98, Trento, Itália, Junho de 1998. p. 3-15
JOACHIMS, T. 1997. A probabilistic analysis of the Rocchio algorithm with TFIDF for text categorization. IN: Proceedings International Conference on Machine Learning, ICML-97, Nashville, 1997. p.143-151.
KHAN, Faisal M. ET AL. 2002. Mining chat-room conversations for social and semantic interactions. Technical Report, LU-CSE-02-011, Lehigh University.
KNIGHT, Kevin. 1999. Mining online text. Communications of the ACM, v.42, n.11, p.58-61.
LANG, K. 1995. NewsWeeder: learning to filter netnews. IN: Proceedings International Conference on Machine Learning, ICML-95, 12., Lake Tahoe, 1995. p.331-339.
LEWIS, David D. 1998. Naive (bayes) at forty: The independence assumption in information retrieval. In: European Conference on Machine Learning, Chemnitz, Alemanha, 1998. p.4-15. (Lecture Notes in Computer Science, v.1398).
LOH, S.; WIVES, L. K.; OLIVEIRA, J. P. M. 2000. Concept-based knowledge discovery in texts extracted from the Web. ACM SIGKDD Explorations, v.2, n.1, Julho de 2000, p. 29-39.
McCALLUM, A. K. & NIGAM, K. 1998. Employing EM in pool-based active learning for text classification. IN: Proceedings International Conference on Machine Learning, ICML-98, Madison, 1998. p.350-358.
McCALLUM, A. K.; ROSENFELD, R.; MITCHELL, T. M.; NG, A. Y. 1998. Improving text classification by shrinkage in a hierarchy of classes. IN: Proceedings International Conference on Machine Learning, ICML-98, Madison, 1 998. p.359-367.
NIGAM, K.; McCALLUM, A. K.; THRUN, S.; MITCHELL, T. M. 2000. Text classification from labeled and unlabeled documens using EM. Machine Learning, v. 39, n.2/3, p.103-134.
RAGAS, Hein & KOSTER, Cornelis H. A. 1998. Four text classification algorithms compared on a Dutch corpus. In: International ACM-SIGIR Conference on Research and Development in Information Retrieval, Melbourne, 1998, p.369-370.
RILOFF, Ellen & LEHNERT, Wendy. 1994. Information extraction as a basis for high-precision text classification. ACM Transactions on Information Systems, v.12, n.3, Julho de 1994, p.296-333.
ROCCHIO, J. J. 1966. Document retrieval systems-optimization and evaluation. Tese (Doutorado)-Harvard University, Cambridge.
SALTON, G. & McGILL, M. J. 1983. Introduction to modern information retrieval. New York: McGraw-Hill, 1983.
SEBASTIANI, Fabrizio. 2002. Machine learning in automated text categorization. ACM Computing Surveys, v.34, n.1, Março de 2002.
SCHAPIRE, R. E. & SINGER, Y. 2000. BoosTexter: a boosting-based system for text categorization. Machine Learning, v. 39, n.2/3, p.135-168.
SOWA, John F. 2002. Building, sharing, and merging ontologies. Disponível em [link]
Publicado
31/07/2004
Como Citar
LOH, Stanley; LICHTNOW, Daniel; SALDAÑA, Ramiro; BORGES, Thyago; PRIMO, Tiago; KICKHÖFEL, Rodrigo Branco; SIMÕES, Gabriel.
Investigação sobre a Identificação de Assuntos em Mensagens de Chat. In: SIMPÓSIO BRASILEIRO DE TECNOLOGIA DA INFORMAÇÃO E DA LINGUAGEM HUMANA (STIL), 2. , 2004, Salvador/BA.
Anais [...].
Porto Alegre: Sociedade Brasileira de Computação,
2004
.
p. 20-29.
