Statistical inference method of user preference on broadcasting content

Cited 3 time in webofscience Cited 0 time in scopus
  • Hit : 188
  • Download : 0
This paper proposes a novel approach for estimating the statistical multimedia user preference by providing weights to multimedia contents with respective to their consumed time. The optimal weights can be obtained by training the statistical system in the sense that the mutual information between old preference and current preference is maximized. The weighting scheme can be done by partitioning a user's consumption history data into smaller sets in a time axis. With developing a mathematical derivation of our learning method, experiments were implemented for predicting the TV genre preference using 2,000 TV viewers' watching history and showed that the performance of our method is better than that of the typical method.
Publisher
SPRINGER-VERLAG BERLIN
Issue Date
2005
Language
English
Article Type
Article; Proceedings Paper
Citation

COMPUTATIONAL SCIENCE - ICCS 2005, PT 1, PROCEEDINGS BOOK SERIES: LECTURE NOTES IN COMPUTER SCIENCE, v.3514, pp.971 - 978

ISSN
0302-9743
URI
http://hdl.handle.net/10203/89361
Appears in Collection
EE-Journal Papers(저널논문)
Files in This Item
There are no files associated with this item.
This item is cited by other documents in WoS
⊙ Detail Information in WoSⓡ Click to see webofscience_button
⊙ Cited 3 items in WoS Click to see citing articles in records_button

qr_code

  • mendeley

    citeulike


rss_1.0 rss_2.0 atom_1.0