Finding identity group "fingerprints" in documents

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

Volumn 5158 LNCS, Issue , 2008, Pages 113-121

  Booker, Lashon B ^a  

^a MITRE CORPORATION   (United States)

Author keywords

Authorship analysis; Document classification; Latent dirichlet allocation; Topic analysis

Indexed keywords

SECURITY OF DATA; TECHNICAL PRESENTATIONS;

AUTHORSHIP ANALYSES; AUTHORSHIP ANALYSIS; DOCUMENT CLASSIFICATION; DOCUMENT CLASSIFICATIONS; DOCUMENT COLLECTIONS; LATENT DIRICHLET ALLOCATION; SOCIAL IDENTITIES; TOPIC ANALYSIS;

INFORMATION RETRIEVAL SYSTEMS;

EID: 54249156470     PISSN: 03029743     EISSN: 16113349     Source Type: Book Series    
DOI: 10.1007/978-3-540-85303-9_11     Document Type: Conference Paper

References (10)

1. Blei, D., Ng, A., Jordan, M.: Latent Dirichlet Allocation. Journal of Machine Learning Research 3, 993-1022 (2003)
2. Borner, K., Dall'asta, L., Ke, W., Vespignani, A.: Studying the Emerging Global Brain: Analyzing and Visualizing the Impact of Co-Authorship Teams. Complexity 10(4), 57-67 (2005)
3. De Vel, O., Anderson, A., Corney, M., Mohay, G.: Mining E-mail Content for Author Identification Forensics. SIMOD Record 30(4), 55-64 (2001)
4. Griffiths, T., Steyvers, M.: Finding scientific topics. Proceedings of the National Academy of Science 101, 5228-5235 (2004)
5. Griffiths, T., Steyvers, M., Tenenbaum, J.: Topics in semantic representation. Psychological Review 114(2), 211-244 (2007)
6. Joachims, T.: Making large-scale SVM learning practical. In: Schölkopf, B., Burges, C., Smola, A. (eds.) Advances in Kernel Methods - Support Vector Learning. MIT Press, Cambridge (1999)
7. Littlestone, N.: Learning quickly when irrelevant attributes abound: A new linear-threshold algorithm. Machine Learning 2(4), 285-318 (1988)
8. Morik, K., Brockhausen, P., Joachims, T.: Combining statistical learning with a knowledge-based approach - A case study in intensive care monitoring. In: Proceedings of the 16th International Conference on Machine Learning, pp. 268-277. Morgan Kaufmann, San Francisco (1999)
9. Schler, J., Koppel, M., Argamon, S., Pennebaker, J.: Effects of Age and Gender on Blog-ging. In: Computational Approaches to Analyzing Weblogs: Papers from the 2006 AAAI Spring Symposium. AAAI Press, Menlo Park (2006)
10. Stokar von Neufom, D., Franke, K.: Reading Between the Lines: Human-centered Classification of Communication Patterns and Intentions. In: Liu, H., Salerno, J., Young, M. (eds.) Social Computing, Behavioral Modeling, and Prediction. Springer, New York (2008)