Social Attentive Network for Live Stream Recommendation

Dung Ru Yu, Chiao Chuan Chu, Hsu Chao Lai, Jiun Long Huang

研究成果: Conference contribution同行評審

1 引文 斯高帕斯(Scopus)

摘要

Live streaming platforms not only provide live videos but also allow social interactions between viewers via real-time chatting. However, none of existing research has studied the social impact for recommending live streams. In this work, we formulate a new personalized recommendation problem by factoring in both video and social contents (chats). Accordingly, we 1) design a new attention network ANSWER to identify viewers' attention on video and social contents, and 2) rank the channels based on the attentive features. We collect a real dataset from Twitch for evaluation. The experimental results manifest that ANSWER outperforms baselines by at least 26.6% in terms of NDCG@5.

原文English
主出版物標題The Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020
發行者Association for Computing Machinery
頁面24-25
頁數2
ISBN(電子)9781450370240
DOIs
出版狀態Published - 20 4月 2020
事件29th International World Wide Web Conference, WWW 2020 - Taipei, Taiwan
持續時間: 20 4月 202024 4月 2020

出版系列

名字The Web Conference 2020 - Companion of the World Wide Web Conference, WWW 2020

Conference

Conference29th International World Wide Web Conference, WWW 2020
國家/地區Taiwan
城市Taipei
期間20/04/2024/04/20

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