Data processing: artificial intelligence – Miscellaneous
Reexamination Certificate
2007-09-04
2007-09-04
Knight, Anthony (Department: 2121)
Data processing: artificial intelligence
Miscellaneous
C700S103000, C700S093000, C700S108000
Reexamination Certificate
active
10757978
ABSTRACT:
A predictive modeling system and methodology makes predictions using unstructured content as an input, either alone or in conjunction with structured content. Content transformation rules are selected for application to the unstructured content, such as emails, call center notes, and other forms of human communication, by identifying the rules that are likely to improve the performance of a predictive modeling system.
REFERENCES:
patent: 5937192 (1999-08-01), Martin
patent: 6298174 (2001-10-01), Lantrip et al.
patent: 6546379 (2003-04-01), Hong
patent: 6597775 (2003-07-01), Lawyer
patent: 6772170 (2004-08-01), Pennock et al.
patent: 2003/0236691 (2003-12-01), Casati
patent: 2004/0049473 (2004-03-01), Gower
patent: 2004/0049478 (2004-03-01), Jasper et al.
Azari et al., Actions, Answers, and Uncertainty: A Decision-Making Perspective on Web-Based Question Answering, Proceedings of the Conference on Uncertainty and Artificial Intelligence, 2003, pp. 11-19.
Brill et al., Data-Intensive Question Answering, 2001, Microsoft Research.
ORACLE, 20 OLAP and Data Mining, 1996, 2002, Oracle 9i Data Warehousing Guide Release 2 (9.2).
Dittrich et al., The Active Database Management System Manifesto: A Rulebase of ADBMS Features, In T. Sellis (ed.): Proc. 2nd Workshop on Rules in Databases (RIDS), Athens, Greece, Sep. 1995. Lecture Notes in Computer Science, Springer 1995.
Leavitt N.,Data Mining for the Corporate Masses? Industry Trends, IEEE, Computer, May 2002 (vol. 35, No. 5) p. 22-24.
Galavott L., Sebastiani F., Simi M.,Experiments on the Use of Feature Selection and Negative Evidence in Automated Text Categorization, Proceedings of ECDL-00, 4thEuropean Conference on Research and Advanced Technology for Digital Libraries, Springer, Verlag, Heidelberg, DE, Lisbon, PT, 2000, pp. 59-68.
Apte C.V., Hong S.J., Natarajan R., Pednault E.P.D., Tipu F.A., Weiss S.M.,Data-Intensive Analytics For Predictive Modeling, IBM J. Res. & Dev. vol. 47 No. 1, Jan. 2003, p. 17-23.
Young Nahm U. and J. Mooney R., Using Information Extraction to Aid the Discovery of Prediction Rules from Text, In Proceedings of the Sixth International Conference on Knowledge Discovery and Data Mining (KDD-2000) Workshop on Text Mining, pp. 51-58, Boston, MA, Aug. 2000.
Jacobsen Matthew S.
Jasper Robert J.
Meyer Michael M.
Pennock Kelly A.
Brown, Jr. Nathan H.
Fenwick & West LLP
Intelligent Results
Knight Anthony
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