Data processing: financial – business practice – management – or co – Automated electrical financial or business practice or... – Discount or incentive
Reexamination Certificate
2008-07-22
2008-07-22
Jeanty, Romain (Department: 3623)
Data processing: financial, business practice, management, or co
Automated electrical financial or business practice or...
Discount or incentive
C706S014000, C705S014270
Reexamination Certificate
active
07403904
ABSTRACT:
A system and method for sequential decision-making for customer relationship management includes providing customer data including stimulus-response history data, and automatically generating actionable rules based on the customer data. Further, automatically generating actionable rules may include estimating a value function using reinforcement learning.
REFERENCES:
patent: 6519571 (2003-02-01), Guheen et al.
patent: 6970830 (2005-11-01), Samra et al.
patent: 7003476 (2006-02-01), Samra et al.
patent: 7006979 (2006-02-01), Samra et al.
patent: 7010495 (2006-03-01), Samra et al.
patent: 2002/0133391 (2002-09-01), Johnson
patent: 2003/0204368 (2003-10-01), Ertin et al.
patent: 2005/0071223 (2005-03-01), Jain et al.
patent: WO0129692 (2001-04-01), None
Malhotra et al. “Marketing Research: . . . for the Twenty-First Century,” Journal of the Academy of Marketing Science, vol. 27, No. 1, pp. 160-183.
Little, John D. C. Marketing Automation on the Internet. 5th Invitational Choice Symposium, UC Berkeley, Jun. 1-5, 2001 [slide presentation].
Littman, Michael L. Algorithms for Sequential Decision Making. Ph. D. Dissertation, Department of Computer Science, Brown University, Mar. 1996.
Ribeiro, C. Artificial Intelligence Review. May 2002, vol. 17, Issue 3 (abstract only).
Georges, and Milley (“KDD'99 Competition: Knowledge Discovery Contest”, ACM SIGKDD Explorations, Jan. 2000 (pp. 79-84).
Boyan, Justin A. Learning Evaluation Functions for Global Optimization, PhD Dissertation, CMU-CS-98-152, Aug. 1, 1998 (pp. 1-41).
Szepesvair, Csaba and Littman, Michael L. Generalized Markov Decision Processes: Dynamic Programming and Reinforcement Learning Algorithms, Technical Report CS-96-11, Brown University, Nov. 25, 1997.
Xin Wang et al., “Efficient Value Function Approximation Using Regression Trees”, Department of Computer Science, Oregon State University, Corvallis, Oregon, pp. 1-11.
John N. Tsitsiklis et al., “An Analysis of Temporal-Difference Learning with Function Approximation”, Laboratory for Information and Decision Systems, Massachusetts Institute of Technology, Cambridge, MA, pp. 1-32.
Pedro Domingos, “Meta Cost: A General Method for Making Classifiers Cost-Sensitive”, Artificial Intelligence Group.
Wei Fan et al., “A Framework for Scalable cost-sensitive Learning Based on Combining Probabilities and Benefits”, IBM T.J. Watson Research.
Wei Fan et al., “AdaCost: Misclassification Cost-sensitive Boosting”, Computer Science Department., Columbia University, New Y ork, NY.
Christopher J.C.H. Watkins et al., “Technical Note Q-Learning”, Machine Learning 1992, pp. 55-68.
Leslie Pack Kaelbling et al., “Reinforcement Learning: A Survey”,Journal of Artificial Intelligence Reserach 4(1996), pp. 237-285.
G.A. Rummery et al., “On-Line Q-Learning Using Connectionist Systems”, Cambridge University Engineering Department, England, Sep. 1994, pp. 1-20.
Dragos D. Margineantu et al., “Bootstrap Methods for the Cost-Sensitive Evaluation of Classifiers”, Department of Computer Science, Oregon State University, Corvallis, OR.
Bianca Zadrozny et al., “Learning and Making Decisions When Costs and Probabilities are Both Unknown”, Department of Computer Science and Engineering, University of California, San Diego La Jolla, CA.
Charles Elkan, “The Foundation of Cost-Sensitive Learning”, Department of Computer Science and Engineering, University of California, San Diego La Jolla, CA.
“Cost-Sensitive Learning Bibliography”, http://home.ptd.net/•olcay/cost-sensitive.html, Nov. 26, 2002, pp. 1-7.
C. Apte et al., “Segmentation-Based Modeling for Advanced Targeted Marketing”, IBM Research Division, pp. 1-10, Mar. 8, 2001.
Abe Naoki
Pednault Edwin P. D.
International Business Machines - Corporation
Jeanty Romain
Kaufman, Esq. Stephen C.
McGinn IP Law Group PLLC
Robertson Dave
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