Data classification using stochastic key feature generation

Details Data classification using stochastic key feature generation Data classification using stochastic key feature generation

2007-04-24

2007-04-24

Hirl, Joseph P (Department: 2129)

Data processing: artificial intelligence

Knowledge processing system

C706S012000, C706S046000

Reexamination Certificate

active

10666754

ABSTRACT:
Data classification using stochastic key feature generation includes obtaining a set of training data having associated summaries. The set of training data and associated summaries are used to generate a key feature generation model. Another set of training data having associated categories is also obtained, and the key feature generation model is used to map this other set of training data to a set of vectors. A data classifier is then trained based on the set of vectors and the associated categories.

REFERENCES:
patent: 7020642 (2006-03-01), Ferguson et al.
patent: 2003/0069877 (2003-04-01), Grefenstette et al.
patent: 2003/0078899 (2003-04-01), Shanahan
patent: 2004/0015462 (2004-01-01), Lienhart et al.
patent: 2004/0019575 (2004-01-01), Talbot et al.
patent: 2004/0024719 (2004-02-01), Adar et al.
patent: 2004/0024721 (2004-02-01), Donovan et al.
patent: 2006/0089924 (2006-04-01), Raskutti et al.
Dragomir Radev et al, Evaluation of Text Summarization in a Cross-lingual Information Retrieval Framework, 2001, Johns Hopkins University, 1-135.
Ting Fie et al, Question Classification for E-learning by Artifical Neural Network, 2003, IEEE, 0-7803-8185-8/03, 1757-1761.
Dragomir Radev, Simone Teufel Horacio Saggion, Wai Lam, John Blitzer, Arda Celebi, Hong Qi, Elliot Drabek, and Danyu Liu, “Evaluation of Text Summarization in a Crosslingual Information Retrieval Framework”, Summer 2001 Johns Hopkins Workshop Final Report, pp. 1-135.
Dumais, S., Platt, J., Heckerman, D., & Sahami, M. (1998). “Inductive Learning Algorithms and Representations for Text Categorization.” In Proceedings of the Seventh ACM International Conference on Information and Knowledge Management, pp. 148-155.
Liu, H. & Motoda, H. (1998). “Feature Transformation and Subset Selection.” IEEE Intelligent System, vol. 13, No. 2, pp. 26-28.

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