A Topic-Based Recommender System for Electronic Marketplace Platforms

A large number of items are placed, bought and sold every day in auction marketplaces across the web. The amount of information and the number of available items makes finding what to buy, as well as describing an item to sell, a challenge for the participants. In this paper we propose a topic-based recommender system that exploits the latent semantics in the item descriptions in order to support the activities of buyers and sellers in auction electronic marketplaces. We present the design of our system and demonstrate how it can be used in real life scenarios.

[1]  Ralf Krestel,et al.  Latent dirichlet allocation for tag recommendation , 2009, RecSys '09.

[2]  Yehuda Koren,et al.  Matrix Factorization Techniques for Recommender Systems , 2009, Computer.

[3]  Michael I. Jordan,et al.  Latent Dirichlet Allocation , 2001, J. Mach. Learn. Res..

[4]  Robin D. Burke,et al.  Hybrid Recommender Systems: Survey and Experiments , 2002, User Modeling and User-Adapted Interaction.

[5]  Zhigeng Pan,et al.  Content-Based Recommendation in E-Commerce , 2005, ICCSA.

[6]  Yoon Ho Cho,et al.  A personalized recommender system based on web usage mining and decision tree induction , 2002, Expert Syst. Appl..

[7]  H. Wang,et al.  A multi-agent-based model for a negotiation support system in electronic commerce , 2007, Enterp. Inf. Syst..

[8]  Kyoung-jae Kim,et al.  A recommender system using GA K-means clustering in an online shopping market , 2008, Expert Syst. Appl..

[9]  Greg Linden,et al.  Amazon . com Recommendations Item-to-Item Collaborative Filtering , 2001 .

[10]  Yang Weng,et al.  Design and implementation of web-based DSS for online shopping mall , 2009, 2009 IEEE International Conference on Control and Automation.

[11]  Hsinchun Chen,et al.  A comparison of collaborative-filtering algorithms for ecommerce , 2007 .

[12]  Wei-Po Lee,et al.  Towards agent-based decision making in the electronic marketplace: interactive recommendation and automated negotiation , 2004, Expert Syst. Appl..

[13]  Thomas L. Griffiths,et al.  Probabilistic Topic Models , 2007 .

[14]  Jose Jesus Castro-Schez,et al.  A highly adaptive recommender system based on fuzzy logic for B2C e-commerce portals , 2011, Expert Syst. Appl..

[15]  Hsiao-Fan Wang,et al.  A strategy-oriented operation module for recommender systems in E-commerce , 2009, Comput. Oper. Res..

[16]  Gerard Salton,et al.  A vector space model for automatic indexing , 1975, CACM.

[17]  Douglas M. Lambert,et al.  Internet-enabled coordination in the supply chain , 2003 .

[18]  John Riedl,et al.  Analysis of recommendation algorithms for e-commerce , 2000, EC '00.

[19]  HofmannThomas.  Latent semantic models for collaborative filtering , 2004 .

[20]  Shiu-li Huang,et al.  Designing utility-based recommender systems for e-commerce: Evaluation of preference-elicitation methods , 2011, Electron. Commer. Res. Appl..

[21]  Hsiao-Fan Wang,et al.  A mathematical model for product selection strategies in a recommender system , 2009, Expert Syst. Appl..

[22]  Mark Steyvers,et al.  Finding scientific topics , 2004, Proceedings of the National Academy of Sciences of the United States of America.

[23]  Ramesh Nallapati,et al.  Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora , 2009, EMNLP.

[24]  Hossein Sharifi,et al.  A classification and selection model of e-marketplaces for better alignment of supply chains , 2006, J. Enterp. Inf. Manag..

[25]  B. Schwartz.  The Paradox of Choice: Why More Is Less , 2004 .

[26]  Hsinchun Chen,et al.  A Comparison of Collaborative-Filtering Recommendation Algorithms for E-commerce , 2007, IEEE Intelligent Systems.

[27]  A. M. Madni,et al.  Recommender systems in e-commerce , 2014, 2014 World Automation Congress (WAC).

[28]  Maks Ovsjanikov,et al.  Topic Modeling for Personalized Recommendation of Volatile Items , 2010, ECML/PKDD.

[29]  Pu-Jen Cheng,et al.  Title-Based Product Search - Exemplified in a Chinese E-commerce Portal , 2010, AIRS.

[30]  Deborah L. McGuinness,et al.  Ontologies and Electronic Commerce , 2001, IEEE Intell. Syst..

[31]  Gediminas Adomavicius,et al.  Toward the next generation of recommender systems: a survey of the state-of-the-art and possible extensions , 2005, IEEE Transactions on Knowledge and Data Engineering.

[32]  Thomas Hofmann,et al.  Latent semantic models for collaborative filtering , 2004, TOIS.

[33]  Steven Walczak,et al.  Auction Advisor: an agent-based online-auction decision support system , 2006, Decis. Support Syst..

[34]  Yannis Bakos,et al.  The emerging role of electronic marketplaces on the Internet , 1998, CACM.

[35]  Ruslan Salakhutdinov,et al.  Evaluation methods for topic models , 2009, ICML '09.

[36]  Martin Grieger.  Electronic marketplaces: A literature review and a call for supply chain management research , 2003, Eur. J. Oper. Res..

[37]  Hsinchun Chen,et al.  A graph model for E-commerce recommender systems , 2004, J. Assoc. Inf. Sci. Technol..

[38]  Giuseppe M. L. Sarnè,et al.  A multi-agent recommender system for supporting device adaptivity in e-Commerce , 2011, Journal of Intelligent Information Systems.

[39]  John D. Lafferty,et al.  Dynamic topic models , 2006, ICML.

[40]  Robin Burke,et al.  Knowledge-based recommender systems , 2000 .