Abstract
Due to the substantial growth of IPTV video users, the weak characteristics of terminal "Set-Top-Box + TV" lead to a great difficulty for users to search required videos, and effective recommendation has an important influence on improving VOD quality. In this paper, the Forecast algorithm is proposed, which is based on the sequential pattern method, consider timeliness features of the videos, convert user watch history into relative access value, then do personalized recommendation. It has strong response speed, can basically meet the needs of real-time video recommendation on IPTV. The algorithm is easy to understand, has good recommend result.
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© 2012 Springer Science+Business Media Dordrecht
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Fan, N., Yang, Y., He, L. (2012). An Algorithm of Users Access Patterns Mining Based on Video Recommendation. In: Park, J., Jin, Q., Sang-soo Yeo, M., Hu, B. (eds) Human Centric Technology and Service in Smart Space. Lecture Notes in Electrical Engineering, vol 182. Springer, Dordrecht. https://doi.org/10.1007/978-94-007-5086-9_5
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DOI: https://doi.org/10.1007/978-94-007-5086-9_5
Publisher Name: Springer, Dordrecht
Print ISBN: 978-94-007-5085-2
Online ISBN: 978-94-007-5086-9
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