Hot Topic Extraction Based on Timeline Analysis and Multidimensional Sentence Modeling
IEEE Transactions on Knowledge and Data Engineering
Time-dependent event hierarchy construction
Proceedings of the 13th ACM SIGKDD international conference on Knowledge discovery and data mining
Searching blogs and news: a study on popular queries
Proceedings of the 31st annual international ACM SIGIR conference on Research and development in information retrieval
Effective and Efficient Query Processing for Video Subsequence Identification
IEEE Transactions on Knowledge and Data Engineering
Real-time large scale near-duplicate web video retrieval
Proceedings of the international conference on Multimedia
Beyond search: Event-driven summarization for web videos
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
Detection and location of near-duplicate video sub-clips by finding dense subgraphs
MM '11 Proceedings of the 19th ACM international conference on Multimedia
Visual memes in social media: tracking real-world news in YouTube videos
MM '11 Proceedings of the 19th ACM international conference on Multimedia
A unified framework for web video topic discovery and visualization
Pattern Recognition Letters
Query-Guided Event Detection From News and Blog Streams
IEEE Transactions on Systems, Man, and Cybernetics, Part A: Systems and Humans
Cross-media topic detection associated with hot search queries
Proceedings of the Fifth International Conference on Internet Multimedia Computing and Service
Socially motivated multimedia topic timeline summarization
Proceedings of the 2nd international workshop on Socially-aware multimedia
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The efficient organization and navigation of web videos in the topic level could enhance the user experience and boost the user's understanding about the happened events. Due to the potential application prospects, topic detection attracts increasing research interests in the last decade. On one hand, the user concerned real world hot topic always leads to a massive discussion in the video sharing sites, such as YouTube, Youku, etc. On the other hand, the search volume of the topic related keywords are growing explosively in the search engine such as Google, Yahoo, etc. These keywords are the queries formulated by the users to search their concerned topics. They reflect the users' intention and could be used as a clue to find the hot topics. In this paper, different from the traditional topic detection methods, which mainly rely on data clustering, we propose a novel multi-clue fusion approach for web video topic detection. In our approach, firstly by utilizing the video related tag information, a maximum average score and a burstiness degree are proposed to extract the dense-bursty tag groups. Secondly, the near-duplicate keyframes (NDK) are extracted from the videos and fused with the extracted tag groups. After that, the hot search keywords from the search engine are used as guidance for topic detection. Finally, these clues are combined together to detect the topics hidden in the web video data. Experiment is conducted on the YouTube video data and the results demonstrate that the proposed method is effective.