Intelligent page recommender agents: real-time content delivery for articles and pages related to similar topics

Authors:
Robin M. E. Swezey;Shun Shiramatsu;Tadachika Ozono;Toramatsu Shintani
Affiliations:
Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan;Graduate School of Engineering, Nagoya Institute of Technology, Nagoya, Aichi, Japan
Venue:
IEA/AIE'11 Proceedings of the 24th international conference on Industrial engineering and other applications of applied intelligent systems conference on Modern approaches in applied intelligence - Volume Part II
Year:
2011

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Abstract

In this paper, we present an architecture and sample implementation of a system which allows us to push latest up-to-date related contents to any Web news article or page in real-time. The architecture makes use of page Agents which recommend the contents and are persistent as well as synchronized over all page instances in browsers. The Agents are easy to incorporate on any Web page and make use of state-of-the-art Web technology. In our sample implementation, we show how our Agents, coupled with a Complementary Naive Bayes classifier, can recommend latest contents related to 47 Japanese prefectures and over 1700 Japanese cities. We show performance results and conclude on further research to improve the affiliate and user experience on the Web.