Improving Video Recommendation Systems from Implicit Feedback in the E-marketing Environment

J.H. Zhang, W. Chong, O. Liu, K.L. Man

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

Abstract

Because of the overload of information, it is necessary for online video websites to develop effective recommendation systems to help video users find out the videos of interest efficiently. Furthermore, due to the lack of explicit feedback, implicit feedback will play an important role in the development of video recommendation systems. Based on past research, this paper tries to discover the implicit interest indicators that can indicate video users’ interest based on gender. These implicit interest indicators are broadly comprised of cursor movements, scrolling activities and mouse speed.
Original languageEnglish
Title of host publication2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017
Pages723-727
Publication statusPublished - 17 Mar 2017
Event2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 - Hong Kong, Hong Kong
Duration: 15 Mar 201717 Mar 2017

Publication series

NameLecture Notes in Engineering and Computer Science
Volume2228

Conference

Conference2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017
CountryHong Kong
CityHong Kong
Period15/03/1717/03/17

Fingerprint Dive into the research topics of 'Improving Video Recommendation Systems from Implicit Feedback in the E-marketing Environment'. Together they form a unique fingerprint.

  • Cite this

    Zhang, J. H., Chong, W., Liu, O., & Man, K. L. (2017). Improving Video Recommendation Systems from Implicit Feedback in the E-marketing Environment. In 2017 International MultiConference of Engineers and Computer Scientists, IMECS 2017 (pp. 723-727). (Lecture Notes in Engineering and Computer Science; Vol. 2228). http://www.iaeng.org/publication/IMECS2017/IMECS2017_pp723-727.pdf