A Multi-task Multi-kernel Transfer Learning Method for Customer Response Modeling in Social Media

Minghe Sun (), Zhen-Yu Chen and Zhi-Ping Fan
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Minghe Sun: UTSA

Working Papers from College of Business, University of Texas at San Antonio

Abstract: Customer response modeling is essential for a firm to allocate the marketing resources to active customers who have potential values. With the development of social media, customer response modeling in social media plays important roles in the firms’ marketing decisions. For customer response modeling in social media, the inputs involve multiple types of data and the purposes are to identify respondents to multiple items. In this study, a multi-task multi-kernel transfer learning (MT-MKTL) method is proposed to integrate shared, task-specific and transferred features in a framework for customer response modeling in social media. A two-phase algorithm is applied to solving the MT-MKTL problem. A computational experiment is conducted on microblog data. The experimental results show that the MT-MKTL method exhibits good performance.

Keywords: Customer response modeling; Social media; Multi-task learning; Transfer learning; Multi-kernel learning (search for similar items in EconPapers)
JEL-codes: C32 C38 C51 C61 (search for similar items in EconPapers)
Pages: 13 pages
Date: 2014
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