TY - GEN
T1 - An algorithm of users access patterns mining based on video recommendation
AU - Fan, Na
AU - Yang, Yan
AU - He, Liang
PY - 2012
Y1 - 2012
N2 - 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.
AB - 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.
KW - Access mode
KW - Data mining
KW - Recommend on video
KW - Sequence
UR - https://www.scopus.com/pages/publications/84870729408
U2 - 10.1007/978-94-007-5086-9_5
DO - 10.1007/978-94-007-5086-9_5
M3 - 会议稿件
AN - SCOPUS:84870729408
SN - 9789400750852
T3 - Lecture Notes in Electrical Engineering
SP - 37
EP - 42
BT - Human Centric Technology and Service in Smart Space, HumanCom 2012
T2 - 2012 International Conference on Human-Centric Computing, HumanCom 2012
Y2 - 6 September 2012 through 8 September 2012
ER -