Multimedia recommendation

Jialie Shen, Meng Wang, Shuicheng Yan, Peng Cui

Research output: Chapter in Book/Report/Conference proceedingConference Paper published in Proceedings

Abstract

Due to the rapid growth of online multimedia information, the problem of information overload has become more and more serious in recent decades. To address this problem, various multimedia recommendation technologies have been developed by different research communities (e.g., multimedia systems, information retrieval, and machine learning). Meanwhile, many commercial web systems (e.g., Flick, Youtube, and Last.fm) have successfully applied recommendation techniques to provide users personalized multimedia content and services in a convenient and flexible way. This tutorial focuses on exploring the state-of-the-art in multimedia recommendation. We also discuss the experience gained from developing existing systems and review key challenges associated with large-scale multimedia recommendation.

Original languageEnglish
Title of host publicationMM 2012 - Proceedings of the 20th ACM International Conference on Multimedia
Place of PublicationNara, Japan
PublisherAssociation for Computing Machinery (ACM)
Pages1535
Number of pages1
ISBN (Print)9781450310895
DOIs
Publication statusPublished - 26 Dec 2012
Externally publishedYes
Event20th ACM International Conference on Multimedia, MM 2012 - Nara, Japan
Duration: 29 Oct 20122 Nov 2012

Conference

Conference20th ACM International Conference on Multimedia, MM 2012
CountryJapan
CityNara
Period29/10/122/11/12

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  • Cite this

    Shen, J., Wang, M., Yan, S., & Cui, P. (2012). Multimedia recommendation. In MM 2012 - Proceedings of the 20th ACM International Conference on Multimedia (pp. 1535). Association for Computing Machinery (ACM). https://doi.org/10.1145/2393347.2396554