Building a Book Recommender system using time based content filtering
نویسنده
چکیده
Recommender System are new generation internet tool that help user in navigating through information on the internet and receive information related to their preferences. Although most of the time recommender systems are applied in the area of online shopping and entertainment domains like movie and music, yet their applicability is being researched upon in other area as well. This paper presents an overview of the Recommender Systems which are currently working in the domain of online book shopping. This paper also proposes a new book recommender system that combines user choices with not only similar users but other users as well to give diverse recommendation that change over time. The overall architecture of the proposed system is presented and its implementation with a prototype design is described. Lastly, the paper presents empirical evaluation of the system based on a survey reflecting the impact of such diverse recommendations on the user choices. Key-Words: Recommender system; Collaborative filtering; Content filtering; Data mining; Time; Book
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