Cited By
View all- Gao WTian YHuang TYang Q(2010)VloggingACM Computing Surveys (CSUR)10.1145/1749603.174960642:4(1-57)Online publication date: 23-Jun-2010
Personalized News Video Recommendation Via Interactive Exploration
Pages 380 - 389
Abstract
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 <em>news topics of interest</em> 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.
References
[1]
Yang, B., Mei, T., Hua, X.S., Yang, L., Yang, S.Q., Li, M.: Online video recommendation based on multimodal fusion and relevance feedback. In: ACM CIVR, pp. 73-80 (2007).
[2]
Marchionini, G.: Information seeking in electronic environments. Cambridge University Press, Cambridge (2007).
[3]
Wactlar, H., Hauptmann, A., Gong, Y., Christel, M.: Lessons learned from the creation and deployment of a terabyte digital video library. IEEE Computer 32, 66-73 (1999).
[4]
Luo, H., Fan, J., Yang, J., Ribarsky,W., Satoh, S.: Analyzing large-scale news video databases to support knowledge visualization and intuitive retrieval. In: IEEE Symposium on Visual Analytics Science and Technology (2007).
[5]
Swan, R., Allan, J.: Timemine: visualizing automatically constructed timelines. In: ACM SIGIR (2000).
[6]
Weskamp, M.: Newsmap, http://www.marumushi.com/apps/newsmap/index.cfm
[7]
Havre, S., Hetzler, B., Nowell, L.: Themeriver: Visualizing thematic changes in large document collections. IEEE Trans. on Visualization and Computer Graphics 8, 9-20 (2002).
[8]
Lai, W., Hua, X.S., Ma, W.Y.: Towards content-based relevance ranking for video search. In: ACM Multimedia, pp. 627-630 (2007).
[9]
Teevan, J., Dumais, S., Horvitz, E.: Personalized search via automated analysis of interests and activities. In: ACM SIGIR (2005).
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Published In
December 2008
1195 pages
Publisher
Springer-Verlag
Berlin, Heidelberg
Publication History
Published: 01 December 2008
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View all- Gao WTian YHuang TYang Q(2010)VloggingACM Computing Surveys (CSUR)10.1145/1749603.174960642:4(1-57)Online publication date: 23-Jun-2010