Effective and scalable authorship attribution using function words

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

Volumn 3689 LNCS, Issue , 2005, Pages 174-189

  Zhao, Ying ^a   Zobel, Justin ^a  

^a RMIT UNIVERSITY   (Australia)

Author keywords

[No Author keywords available]

Indexed keywords

DATA HANDLING; DATA MINING; FEATURE EXTRACTION; INFORMATION ANALYSIS; LEARNING SYSTEMS;

AUTHORSHIP ATTRIBUTION; FEATURE BASED TECHNIQUES; FEATURE SELECTION; NEWSWIRE ARTICLES;

DATABASE SYSTEMS;

EID: 33646123296     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/11562382_14     Document Type: Conference Paper

References (27)

1. D. Aha and D. Kibler. Instance-based learning algorithms. Machine Learning, 6:37-66, 1991.
2. H. Baayen, H. V. Halteren, A. Neijt, and F. Tweedie. An experiment in authorship attribution. 6th JADT, 2002.
3. H. Baayen, H. V. Halteren, and F. Tweedie. Outside the cave of shadows: using syntactic annotation to enhance authorship attribution. Literary and Linguistic Computing, 11(3):121-132, 1996.
4. R. Baeza-Yates and B. Ribeiro-Neto. Modern Information Retrieval. Addison-Wesley Longman, May 1999.
5. D. Benedetto, E. Caglioti, and V. Loreto. Language trees and zipping. The American Physical Society, 88(4), 2002.
6. Y. Bernstein and J. Zobel. A scalable system for identifying co-derivative documents. In A. Apostolico and M. Melucci, editors, Proceedings of the String Processing and Information Retrieval Symposium (SPIRE), pages 55-67, Padova, Italy, sep 2004. Springer. Published as LNCS 3246.
7. J. N. G. Binongo. Who wrote the 15th book of oz? an application of multivariate statistics to authorship attribution. Computational Linguistics, 16(2):9-17, 2003.
8. J. Burrows. Word patterns and story shapes: the statistical analysis of narrative style. Literary and linguistic Computing, 2:61-70, 1987.
9. J. Burrows. Delta: a measure of stylistic difference and a guide to likely authorship. Literary and Linguistic Computing, 17:267-287, 2002.
10. J. Diederich, J. Kindermann, E. Leopold, and G. Paass. Authorship attribution with support vector machines. Applied Intelligence, 19(1-2): 109-123, 2003.
11. D. D'Souza, J. Thom, and J. Zobel. Collection selection for managed distributed document databases. Information Processing & Management, 40:527-546, 2004.
12. G. Fung. The disputed federalist papers: Svm feature selection via concave minimization. In Proceedings of the 2003 conference on Diversity in computing, pages 42-46. ACM Press, 2003.
13. J. Goodman. Extended comment on language trees and zipping.
14. D. Harman. Overview of the second text retrieval conference (TREC-2). Information Processing & Management, 31(3):271-289, 1995.
15. D. Heckerman, D. Geiger, and D. Chickering. Learning Bayesian networks: the combination of knowledge and statistical data. Machine Learning, 20:197-243, 1995.
16. D. I. Holmes, M. Robertson, and R. paez. Stephen crane and the new-york tribune: A case study in traditional and non-traditional authorship attribution. Computers and the Humanities, 35(3):315-331, 2001.
17. G. H. John and P. Langley. Estimating continuous distributions in Bayesian classifiers. In Eleventh Conference on Uncertainty in Artificial Intelligence, pages 338-345. Morgan Kaufmann Publisher, 1995.
18. P. Juola and H. Baayen. A controlled-corpus experiment in authorship identification by cross-entropy. Literary and Linguistic Computing, 2003.
19. V. Keselj, F. Peng, N. Gereone, and C. Thomas. N-gram-based author profiles for authorship attribution. In Pasific Association for Computational Linguistics, pages 256-264, 2003.
20. D. V. Khmelev and F. J. Tweedie. Using markov chains for identification of writers. Literary and Linguistic Computing, 16(4):229-307, 2002.
21. P. Langley and S. Sage. Tractable average-case analysis of naive Bayesian classifiers. In Eleventh Conference on Uncertainty in Artificial Intelligence, pages 220-228. Morgan Kaufmann Publisher, 1999.
22. F. Peng, D. Schuurmans, V. Keselj, and S. Wang. Language independent authorship attribution using character level language models. In 10th Conference of the European Chapter of the Association for Computational Linguistics, EACL, 2003.
23. R. Quinlan. C4-5: Programs for Machine Learning. San Mateo, CA: Morgan Kaufmann, 1993.
24. F. Sebastiani. Machine learning in automated text categorization. ACM Comput. Surv., 34(1):1-47, 2002.
25. E. Stamatatos, N. Fakotakis, and G. Kokkinakis. Automatic authorship attribution. In Proceedings of the 9th Conference of the European Chapter of the Association for Computational Linguistics, pages 158-164, 1999.
26. E. Stamatatos, N. Fakotakis, and G. Kokkinakis. Computer-based authorship attribution without lexical measures. Computers and the Humanities, 35(2):193-214, 2001.
27. I. H. Witten and E. Frank. Data Mining: Practical machine learning tools with Java implementations. Morgan Kaufmann, San Francisco, 2000.