Tracking web video topics: Discovery, visualization, and monitoring
Despite the massive growth of web-shared videos in Internet, efficient organization and monitoring of videos remains a practical challenge. While nowadays broadcasting channels are keen to monitor online events, identifying topics of interest from huge volume of user uploaded videos and giving recom...
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2011
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sg-smu-ink.sis_research-73512021-11-23T04:04:21Z Tracking web video topics: Discovery, visualization, and monitoring CAO, Juan NGO, Chong-wah ZHANG, Yong-Dong LI, Jin-Tao Despite the massive growth of web-shared videos in Internet, efficient organization and monitoring of videos remains a practical challenge. While nowadays broadcasting channels are keen to monitor online events, identifying topics of interest from huge volume of user uploaded videos and giving recommendation to emerging topics are by no means easy. Specifically, such process involves discovering of new topic, visualization of the topic content, and incremental monitoring of topic evolution. This paper studies the problem from three aspects. First, given a large set of videos collected over months, an efficient algorithm based on salient trajectory extraction on a topic evolution link graph is proposed for topic discovery. Second, topic trajectory is visualized as a temporal graph in 2-D space, with one dimension as time and another as degree of hotness, for depicting the birth, growth, and decay of a topic. Finally, giving the previously discovered topics, an incremental monitoring algorithm is proposed to track newly uploaded videos, while discovering new topics and giving recommendation to potentially hot topics. We demonstrate the application on three months' videos crawled from YouTube during December 2008 to February 2009. Both objective and user studies are conducted to verify the performance. 2011-12-01T08:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6348 info:doi/10.1109/TCSVT.2011.2148470 https://ink.library.smu.edu.sg/context/sis_research/article/7351/viewcontent/tcsvt11_caojuan.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Topic trajectory mining video recommendation visualization Data Storage Systems Graphics and Human Computer Interfaces |
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Topic trajectory mining video recommendation visualization Data Storage Systems Graphics and Human Computer Interfaces CAO, Juan NGO, Chong-wah ZHANG, Yong-Dong LI, Jin-Tao Tracking web video topics: Discovery, visualization, and monitoring |
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Despite the massive growth of web-shared videos in Internet, efficient organization and monitoring of videos remains a practical challenge. While nowadays broadcasting channels are keen to monitor online events, identifying topics of interest from huge volume of user uploaded videos and giving recommendation to emerging topics are by no means easy. Specifically, such process involves discovering of new topic, visualization of the topic content, and incremental monitoring of topic evolution. This paper studies the problem from three aspects. First, given a large set of videos collected over months, an efficient algorithm based on salient trajectory extraction on a topic evolution link graph is proposed for topic discovery. Second, topic trajectory is visualized as a temporal graph in 2-D space, with one dimension as time and another as degree of hotness, for depicting the birth, growth, and decay of a topic. Finally, giving the previously discovered topics, an incremental monitoring algorithm is proposed to track newly uploaded videos, while discovering new topics and giving recommendation to potentially hot topics. We demonstrate the application on three months' videos crawled from YouTube during December 2008 to February 2009. Both objective and user studies are conducted to verify the performance. |
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CAO, Juan NGO, Chong-wah ZHANG, Yong-Dong LI, Jin-Tao |
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CAO, Juan NGO, Chong-wah ZHANG, Yong-Dong LI, Jin-Tao |
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CAO, Juan |
title |
Tracking web video topics: Discovery, visualization, and monitoring |
title_short |
Tracking web video topics: Discovery, visualization, and monitoring |
title_full |
Tracking web video topics: Discovery, visualization, and monitoring |
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Tracking web video topics: Discovery, visualization, and monitoring |
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Tracking web video topics: Discovery, visualization, and monitoring |
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tracking web video topics: discovery, visualization, and monitoring |
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Institutional Knowledge at Singapore Management University |
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2011 |
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https://ink.library.smu.edu.sg/sis_research/6348 https://ink.library.smu.edu.sg/context/sis_research/article/7351/viewcontent/tcsvt11_caojuan.pdf |
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