NDLI: Temporal Cross-Selling Optimization Using Action Proxy-Driven Reinforcement Learning

Content Provider	IEEE Xplore Digital Library
Author	Nan Li Abe, N.
Copyright Year	2011
Abstract	Customer lifetime value modeling and cross-selling pattern mining are two important areas of data mining applications in marketing sciences. In this paper, we propose a novel approach that can address both of these problems in a unified manner. We propose a variant of reinforcement learning, enhanced with the notion of "action proxy", which is applicable to the cross-selling pattern discovery even in the absence of actions. For action proxies, we consider the target reward (changes) across product categories. The motivation is to optimize the target values of immediate rewards to maximize the expected overall long-term reward. Since the changes are directly tied to the reward, unconstrained formulation would result in unbounded behavior, leading us to constrain the learned policy. The goal is to optimize the target values while keeping their effects on the overall immediate rewards constrained. Experiments on real world data not only verify the effectiveness of our framework, but also provide qualitative study of allocation behavior, with particular emphasis on temporal cross-selling optimization.
Starting Page	259
Ending Page	266
File Size	328787
Page Count	8
File Format	PDF
ISBN	9781467300056
DOI	10.1109/ICDMW.2011.163
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2011-12-11
Publisher Place	Canada
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Learning Lifetime Value Cross-Sell Linear regression Reinforcement Learning Vectors Business Optimization Data mining Mathematical model Markov Decision Process Optimization Business
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
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3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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