Publication Type

Journal Article

Version

publishedVersion

Publication Date

3-2017

Abstract

Social Media has already become a new arena of our lives and involved different aspects of our social presence. Users' personal information and activities on social media presumably reveal their personal interests, which offer great opportunities for many e-commerce applications. In this paper, we propose a principled latent variable model to infer user consumption preferences at the category level (e.g. inferring what categories of products a user would like to buy). Our model naturally links users' published content and following relations on microblogs with their consumption behaviors on e-commerce websites. Experimental results show our model outperforms the state-of-the-art methods significantly in inferring a new user's consumption preference. Our model can also learn meaningful consumption-specific topics automatically.

Keywords

social media, e-commerce websites, consumption preferences, topic model

Discipline

Databases and Information Systems | E-Commerce | Numerical Analysis and Scientific Computing | Social Media

Research Areas

Data Science and Engineering

Publication

IEICE Transactions on Information and Systems

Volume

E100D

Issue

3

First Page

537

Last Page

545

ISSN

0916-8532

Identifier

10.1587/transinf.2016EDP7265

Publisher

Institute of Electronics, Information and Communication Engineers

Copyright Owner and License

Authors

Additional URL

https://doi.org/10.1587/transinf.2016EDP7265

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