IFUP: Workshop on multi-dimensional information fusion for user modeling and personalization

Feida Zhu, Yongfeng Zhang, Neil Yorke-Smith, Guibing Guo, Xu Chen

Research output: Chapter in Book/Report/Conference proceedingConference contribution

5 Scopus citations

Abstract

Recommendation system has became an important component in many real applications, ranging from e-commerce, music app to video-sharing site and on-line book store. The key of a successful recommendation system lies in the accurate user/item profiling. With the advent of web 2.0, quite a lot of multimodal information has been accumulated, which provides us with the opportunity to profile users in a more comprehensive manner. However, directly integrating multimodal information into recommendation system is not a trivial task, because they may be either homogenous or heterogeneous, which requires more advanced method for both fusion and alignment. This workshop aims to provide a platform for discussing the challenges and corresponding innovative approaches in fusing multi-dimensional information for user modeling and recommender systems. We hope more advanced technologies can be proposed or inspired, and also we hope that the direction of integrating different types of information can catch much more attention in both academic and industry.

Original languageEnglish (US)
Title of host publicationWSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
PublisherAssociation for Computing Machinery, Inc
Pages804-805
Number of pages2
ISBN (Electronic)9781450355810
DOIs
StatePublished - Feb 2 2018
Event11th ACM International Conference on Web Search and Data Mining, WSDM 2018 - Marina Del Rey, United States
Duration: Feb 5 2018Feb 9 2018

Publication series

NameWSDM 2018 - Proceedings of the 11th ACM International Conference on Web Search and Data Mining
Volume2018-Febuary

Other

Other11th ACM International Conference on Web Search and Data Mining, WSDM 2018
Country/TerritoryUnited States
CityMarina Del Rey
Period2/5/182/9/18

All Science Journal Classification (ASJC) codes

  • Computer Science Applications
  • Software
  • Computer Networks and Communications
  • Information Systems

Keywords

  • Information fusion
  • Multi-dimensional
  • User modeling

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