ICDE '95 Proceedings of the Eleventh International Conference on Data Engineering
RoadRunner: Towards Automatic Data Extraction from Large Web Sites
Proceedings of the 27th International Conference on Very Large Data Bases
ACM Transactions on Internet Technology (TOIT)
Retrieving multimedia web objects based on PageRank algorithm
WWW '05 Special interest tracks and posters of the 14th international conference on World Wide Web
Practical elimination of near-duplicates from web video search
Proceedings of the 15th international conference on Multimedia
I tube, you tube, everybody tubes: analyzing the world's largest user generated content video system
Proceedings of the 7th ACM SIGCOMM conference on Internet measurement
Semantic mining and web service discovery techniques for media resources management
International Journal of Metadata, Semantics and Ontologies
A basis for information retrieval in context
ACM Transactions on Information Systems (TOIS)
SMIL 3.0: Flexible Multimedia for Web, Mobile Devices and Daisy Talking Books
SMIL 3.0: Flexible Multimedia for Web, Mobile Devices and Daisy Talking Books
LeeDeo: Web-Crawled Academic Video Search Engine
ISM '08 Proceedings of the 2008 Tenth IEEE International Symposium on Multimedia
Authoring of scalable multimedia documents
Multimedia Tools and Applications
VideoMap: an interactive video retrieval system of MCG-ICT-CAS
Proceedings of the ACM International Conference on Image and Video Retrieval
A dynamic Petri net model for iterative and interactive distributed multimedia presentation
IEEE Transactions on Multimedia
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Similar contents, duplicates, and segments of videos abound in social media networks. However, querying and aggregating all these data with high quality and personalized demand present increasingly formidable challenges. In the paper, we propose a novel framework for automatically aggregating semantically similar and contextual videos in social media network, which called CLUENET. We use a proactive method to collect and integrate all-around valuable clues centered a video to improve the quality of aggregation; By use of these clues the CLUENET constructs a clues network for video aggregation which extract sequences and similar contents of videos, and uses dynamic Petri net (DPN) to steer video aggregation and data prefetching for adapted to different user's personalized demand. The main features of this framework and how it was implemented using state-of-the-art technologies are also introduced.