We know what you want to buy:a demographic-based system for product recommendation on microblogs


Product recommender systems are often deployed by e-commerce websites to improve user experience and increase sales. However, recommendation is limited by the product information hosted in those e-commerce sites and is only triggered when users are performing e-commerce activities. In this paper, we develop a novel product recommender system called METIS, a MErchanT Intelligence recommender System, which detects users' purchase intents from their microblogs in near real-time and makes product recommendation based on matching the users' demographic information extracted from their public profiles with product demographics learned from microblogs and online reviews. METIS distinguishes itself from traditional product recommender systems in the following aspects: 1) METIS was developed based on a microblogging service platform. As such, it is not limited by the information available in any specific e-commerce website. In addition, METIS is able to track users' purchase intents in near real-time and make recommendations accordingly. 2) In METIS, product recommendation is framed as a learning to rank problem. Users' characteristics extracted from their public profiles in microblogs and products' demographics learned from both online product reviews and microblogs are fed into learning to rank algorithms for product recommendation. We have evaluated our system in a large dataset crawled from Sina Weibo. The experimental results have verified the feasibility and effectiveness of our system. We have also made a demo version of our system publicly available and have implemented a live system which allows registered users to receive recommendations in real time.

Publication DOI: https://doi.org/10.1145/2623330.2623351
Divisions: College of Engineering & Physical Sciences > Systems analytics research institute (SARI)
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Additional Information: Funding: EPSRC (grant EP/L010690/1); National Key Basic Research Program (973 Program) of China under grant No. 2014CB340403, 2014CB340405, NSFC Grant 6127234
Event Title: 20th ACM SIGKDD international conference on Knowledge Discovery and Data mining
Event Type: Other
Event Dates: 2014-08-24 - 2014-08-27
Uncontrolled Keywords: e-commerce,microblog,product demographic,product recommender,Software,Information Systems
ISBN: 978-1-4503-2956-9
Last Modified: 24 Apr 2024 07:27
Date Deposited: 18 Aug 2015 08:05
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Related URLs: http://www.scop ... tnerID=8YFLogxK (Scopus URL)
http://dl.acm.o ... 2623330.2623351 (Publisher URL)
PURE Output Type: Conference contribution
Published Date: 2014-08-04
Authors: Zhao, Xin Wayne
Guo, Yanwei
He, Yulan (ORCID Profile 0000-0003-3948-5845)
Jiang, Han
Wu, Yuexin
Li, Xiaoming



Version: Accepted Version

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