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4th Workshop on Context-Aware Recommender Systems; in conjunction with the 6th ACM Conference on Recommender Systems (RecSys 2012)

ABSTRACT Nowadays there is a variety of TV channels and programs. This seems to be an advantage for the TV user ; but in most cases the user is overwhelmed and not able to choose the most appropriate content though. Assistive systems are needed to support the user in selecting the most appropriate content regarding the user’s interests. The research group Next Generation PVR faced the task to develop a user supporting Personal Video Recorder (PVR) in the form of a Bayesian classifier based recom

Others  :  http://ceur-ws.org/Vol-889/paper6.pdf
PID  :  43409

来源: CEUR

【 摘 要 】

Nowadays there is a variety of TV channels and programs. This seems to be an advantage for the TV user, but in most cases the user is overwhelmed and not able to choose the most appropriate content though. Assistive systems are needed to support the user in selecting the most appropriate content regarding the user’s interests. The research group Next Generation PVR faced the task to develop a user supporting Personal Video Recorder (PVR) in the form of a Bayesian classifier based recommendation system. The work on the prototype of the system is almost done. This paper focuses on the evaluation of the given system. We are presenting two types of evaluation scenarios as well as an approach for measuring user acceptance of a TV recommendation system. Within the evaluation, the acceptance will be questioned. In addition, the results of both scenarios and of the user acceptance survey are presented and discussed.Categories and Subject Descriptors I.2.m [Artificial Intelligence]: Miscellaneous General Terms Algorithms, Experimentation, Human Factors Keywords Recommendation System, Television, Evaluation, Bayesian classifier, User Acceptance 1. INTRODUCTION The way of consuming media clearly changed in recent years. Especially in times of high bandwidth and loads of appropriate media delivering services, the Internet plays an important role in cases of consuming audio/video content. However, live television is still the most popular media. In Germany 97% of all households posses a TV set with an average use of 220 minutes a day [1]. Therefore it is evident that the television market is still interesting for broadcasters. The satellite operator ASTRA holds up to 1700 TV channels just for the region of Germany. Regardless of the encrypted and shopping program, 53 is a realistic number of receivable TV channels [2]. For the TV user it is quite difficult to handle the enormous offer of content. In most cases extensive TV guides list just a limited number of TV channels and often only popular ones. The user will invest time to get an overview of all the available content. Due to too much effort most of the users focus on favored or popular TV channels and the most interesting