Live Multi-Streaming and Donation Recommendations via Coupled Donation-Response Tensor Factorization

Hsu Chao Lai, Jui Yi Tsai, Hong Han Shuai, Jiun Long Huang, Wang Chien Lee, De Nian Yang

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

In contrast to traditional online videos, live multi-streaming supports real-time social interactions between multiple streamers and viewers, such as donations. However, donation and multi-streaming channel recommendations are challenging due to complicated streamer and viewer relations, asymmetric communications, and the tradeoff between personal interests and group interactions. In this paper, we introduce Multi-Stream Party (MSP) and formulate a new multi-streaming recommendation problem, called Donation and MSP Recommendation (DAMRec). We propose Multi-stream Party Recommender System (MARS) to extract latent features via socio-temporal coupled donation-response tensor factorization for donation and MSP recommendations. Experimental results on Twitch and Douyu manifest that MARS significantly outperforms existing recommenders by at least 38.8% in terms of hit ratio and mean average precision.

Original languageEnglish
Title of host publicationCIKM 2020 - Proceedings of the 29th ACM International Conference on Information and Knowledge Management
PublisherAssociation for Computing Machinery
Pages665-674
Number of pages10
ISBN (Electronic)9781450368599
DOIs
StatePublished - 19 Oct 2020
Event29th ACM International Conference on Information and Knowledge Management, CIKM 2020 - Virtual, Online, Ireland
Duration: 19 Oct 202023 Oct 2020

Publication series

NameInternational Conference on Information and Knowledge Management, Proceedings

Conference

Conference29th ACM International Conference on Information and Knowledge Management, CIKM 2020
CountryIreland
CityVirtual, Online
Period19/10/2023/10/20

Keywords

  • donation recommendation
  • live multi-streaming recommendation
  • social-temporal coupled tensor factorization

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