News story clustering from both what and how aspects: Using bag of word model and affinity propagation

Wei Ta Chu, Chao Chin Huang, Wen Fang Cheng

研究成果: Conference contribution

2 引文 斯高帕斯(Scopus)

摘要

The 24-hour news TV channels repeat the same news stories again and again. In this paper we cluster hundreds of news stories broadcasted in a day into dozens of clusters according to topics, and thus facilitate efficient browsing and summarization. The proposed system automatically removes commercial breaks and detects anchorpersons, and then determines boundaries of news stories. Semantic concepts, the bag of visual word model and the bag of trajectory model are used to describe what and how objects present in news stories. After measuring similarity between stories by the earth mover's distance, the affinity propagation algorithm is utilized to cluster stories of the same topic together. The experimental results show that with the proposed methods sophisticated news stories can be effectively clustered.

原文English
主出版物標題MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - AIEMPro 2011 Workshop, AIEMPro'11
頁面7-12
頁數6
DOIs
出版狀態Published - 2011 12月 1
事件2011 ACM Multimedia Conference, MM'11 and Co-Located Workshops - 2011 ACM International Workshop on Automated Media Analysis and Production for Novel TV Services, AIEMPro'11 - Scottsdale, AZ, United States
持續時間: 2011 11月 282011 12月 1

出版系列

名字MM'11 - Proceedings of the 2011 ACM Multimedia Conference and Co-Located Workshops - AIEMPro 2011 Workshop, AIEMPro'11

Conference

Conference2011 ACM Multimedia Conference, MM'11 and Co-Located Workshops - 2011 ACM International Workshop on Automated Media Analysis and Production for Novel TV Services, AIEMPro'11
國家/地區United States
城市Scottsdale, AZ
期間11-11-2811-12-01

All Science Journal Classification (ASJC) codes

  • 電腦繪圖與電腦輔助設計
  • 人機介面

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