Combining contents and citations for scientific document classification

Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Volumn 3809 LNAI, Issue , 2005, Pages 143-152

  Cao, Minh Duc ^a   Gao, Xiaoying ^a  

^a VICTORIA UNIVERSITY OF WELLINGTON   (New Zealand)

Author keywords

[No Author keywords available]

Indexed keywords

DECISION THEORY; INFORMATION ANALYSIS; ITERATIVE METHODS; STATISTICAL METHODS; TEXT PROCESSING; TREES (MATHEMATICS);

DOCUMENT CLASSIFICATION; INFORMATION GAIN; NAIVE BAYES; STATISTICAL CLASSIFICATION;

CLASSIFICATION (OF INFORMATION);

EID: 33745610921     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11589990_17     Document Type: Conference Paper

References (23)

1. Borko, H., Bernick, M.: Automatic document classification. J. ACM 10 (1963) 151-162
2. Sebastiani, F.: Machine learning in automated text categorization. ACM Computing Surveys 34 (2002) 1-47
3. Han, E.-H., Karypis, G.: Centroid-Based Document Classification: Analysis and Experimental Results. Principles of Data Mining and Knowledge Discovery (2000) 424-431
4. Witten, I.H., Frank, E.: Data Mining, Practical Machine Learning Tools and Techniques with Java Implementations. Morgan Kaufmann Publishers (2000)
5. Lewis, D.D.: Naive (Bayes) at forty: The independence assumption in information retrieval. In Nédellec, C., Rouveirol, C., eds.: Proceedings of ECML-98, 10th European Conference on Machine Learning. Number 1398, Chemnitz, DE, Springer Verlag, Heidelberg, DE (1998) 4-15
6. Nigam, K., Lafferty, J., McCallum, A.: Using maximum entropy for text classification. In: IJCAI-99 Workshop on Machine Learning for Information Filtering. (1999) 61-67
7. Wiener, E., Pedersen, L.O., Weigend, A.S.: A neural network approach to topic spotting. In: Proc. of the Symposium on Document Analysis and Information Retrieval. (1995) 317-332
8. Joachims, T.: Text categorization with support vector machines: learning with many relevant features. In Nédellec, C., Rouveirol, C., eds.: Proceedings of ECML-98, 10th European Conference on Machine Learning. Number 1398, Chemnitz, DE, Springer Verlag, Heidelberg, DE (1998) 137-142
9. Mitchell, T.: Machine Learning. McGraw-Hill (1997)
10. Brin, S., Page, L.: The anatomy of a large-scale hypertextual Web search engine. Computer Networks and ISDN Systems 30 (1998) 107-117
11. Getoor, L., Friedman, N., Koller, D., Taskar, B.: Learning probabilistic models of link structure. J. Mach. Learn. Res. 3 (2003) 679-707
12. Taskar, B., Segal, E., Koller, D.: Probabilistic classification and clustering in relational data. In Nebel, B., ed.: Proceeding of IJCAI-01, 17th International Joint Conference on Artificial Intelligence, Seattle, US (2001) 870-878
13. Craven, M., Slattery, S.: Relational learning with statistical predicate invention: Better models for hypertext. Mach. Learn. 43 (2001) 97-119
14. Quinlan, J.R.: Learning logical definitions from relations. Mach. Learn. 5 (1990) 239-266
15. Cohen, W.: Learning to classify English text with ILP methods. In: Advances in Inductive Logic Programming, IOS Press (1996) 124-143
16. Junker, M., Sintek, M., Rinck, M.: Learning for text categorization and information extraction with ILP. In Cussens, J., ed.: Proceedings of the 1st Workshop on Learning Language in Logic, Bled, Slovenia (1999) 84-93
17. Yang, Y., Pedersen, J.O.: A comparative study on feature selection in text categorization. In Fisher, D.H., ed.: Proceedings of ICML-97, 14th International Conference on Machine Learning, Nashville, US, Morgan Kaufmann Publishers, San Francisco, US (1997) 412-420
18. Porter, M.F.: An algorithm for suffix stripping. Readings in Information Retrieval (1997) 313-316
19. McCallum, A.K., Nigam, K., Rennie, J., Seymore, K.: Automating the construction of internet portals with machine learning. Information Retrieval 3 (2000) 127-163
20. McCallum, A., Nigam, K.: A comparison of event models for naive Bayes text classification. In: AAAI-98 Workshop on Learning for Text Categorization. (1998)
21. Lewis, D.D., Ringuette, M.: A comparison of two learning algorithms for text categorization. In: Proceedings of SDAIR-94, 3rd Annual Symposium on Document Analysis and Information Retrieval, Las Vegas, US (1994) 81-93
22. Lewis, D.: An evaluation of prasal and clustered representation of text categorisation tasks. In: Proceedings of SIGIR-92, 15th ACM International Conference on Reseach and Deveplopment in Information Retrieval. (1992) 289-297
23. Chakrabarti, S., Dom, B., Indyk, P.: Enhanced hypertext categorization using hyperlinks. In: SIGMOD '98: Proceedings of the 1998 ACM SIGMOD international conference on Management of data, New York, NY, USA, ACM Press (1998) 307-318