TY - GEN
T1 - Personalized news video recommendation via interactive exploration
AU - Fan, Jianping
AU - Luo, Hangzai
AU - Zhou, Aoying
AU - Keim, Daniel A.
PY - 2008
Y1 - 2008
N2 - In this paper, we have developed an interactive approach to enable personalized news video recommendation. First, multi-modal information channels (audio, video and closed captions) are seamlessly integrated and synchronized to achieve more reliable news topic detection, and the contextual relationships between the news topics are extracted automatically. Second, topic network and hyperbolic visualization are seamlessly integrated to achieve interactive navigation and exploration of large-scale collections of news videos at the topic level, so that users can have a good global overview of large-scale collections of news videos at the first glance. In such interactive topic network navigation and exploration process, the user's personal background knowledge can be taken into consideration for obtaining the news topics of interest interactively, building up their mental models of news needs precisely and formulating their searches easily by selecting the visible news topics on the screen directly. Our system can further recommend the relevant web news, the new search directions, and the most relevant news videos according to their importance and representativeness scores. Our experiments on large-scale collections of news videos have provided very positive results.
AB - In this paper, we have developed an interactive approach to enable personalized news video recommendation. First, multi-modal information channels (audio, video and closed captions) are seamlessly integrated and synchronized to achieve more reliable news topic detection, and the contextual relationships between the news topics are extracted automatically. Second, topic network and hyperbolic visualization are seamlessly integrated to achieve interactive navigation and exploration of large-scale collections of news videos at the topic level, so that users can have a good global overview of large-scale collections of news videos at the first glance. In such interactive topic network navigation and exploration process, the user's personal background knowledge can be taken into consideration for obtaining the news topics of interest interactively, building up their mental models of news needs precisely and formulating their searches easily by selecting the visible news topics on the screen directly. Our system can further recommend the relevant web news, the new search directions, and the most relevant news videos according to their importance and representativeness scores. Our experiments on large-scale collections of news videos have provided very positive results.
KW - Personalized news video recommendation
KW - Topic network
UR - https://www.scopus.com/pages/publications/70149103578
U2 - 10.1007/978-3-540-89646-3_37
DO - 10.1007/978-3-540-89646-3_37
M3 - 会议稿件
AN - SCOPUS:70149103578
SN - 3540896457
SN - 9783540896456
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 380
EP - 389
BT - Advances in Visual Computing - 4th International Symposium, ISVC 2008, Proceedings
PB - Springer Verlag
T2 - 4th International Symposium on Visual Computing, ISVC 2008
Y2 - 1 December 2008 through 3 December 2008
ER -