Live Streaming Channel Recommendation Using HITS Algorithm

Abstract

Live streaming services have been developed prosperously in recent years. With live streaming services, broadcasters broadcast their videos to attract large numbers of viewers to watch. Some live streaming services also provide a platform for viewers gathering together to watch channels and interact with others. Over hundreds of videos broadcast every day, recommending channels are necessary to help viewers finding channels of interests. In this paper, we propose the hybrid HITS algorithm for Channel Recommendation (HyHITS_CR) which adopts the HITS algorithm with modification to utilize the follower-followee relationship on channel recommendation. Besides, we also observe from real logs that some viewers may focus on few particular channels. Thus, HyHITS_CR also takes advantage on such observation to further improve the accuracy of recommendation. Experimental results show that the hit rate of HyHITS_CR is around 10% higher than other prior algorithms.