Discourse segmentation by human and automated means
Computational Linguistics
Text segmentation based on similarity between words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Story boundary detection in large broadcast news video archives: techniques, experience and trends
Proceedings of the 12th annual ACM international conference on Multimedia
A statistical model for domain-independent text segmentation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Evaluation campaigns and TRECVid
MIR '06 Proceedings of the 8th ACM international workshop on Multimedia information retrieval
Using LDA to detect semantically incoherent documents
CoNLL '08 Proceedings of the Twelfth Conference on Computational Natural Language Learning
Text segmentation via topic modeling: an analytical study
Proceedings of the 18th ACM conference on Information and knowledge management
ANSES: summarisation of news video
CIVR'03 Proceedings of the 2nd international conference on Image and video retrieval
Boundary error analysis and categorization in the TRECVID news story segmentation task
CIVR'05 Proceedings of the 4th international conference on Image and Video Retrieval
ICIAP'11 Proceedings of the 16th international conference on Image analysis and processing - Volume Part II
Semantic user modelling for personal news video retrieval
MMM'10 Proceedings of the 16th international conference on Advances in Multimedia Modeling
Multimedia analysis techniques for e-learning
International Journal of Learning Technology
Expert Systems with Applications: An International Journal
Says who?: automatic text-based content analysis of television news
Proceedings of the 2013 international workshop on Mining unstructured big data using natural language processing
Unsupervised text segmentation using LDA and MCMC
AusDM '12 Proceedings of the Tenth Australasian Data Mining Conference - Volume 134
Hi-index | 0.00 |
In this paper, we introduce and evaluate two novel approaches, one using video stream and the other using close-caption text stream, for segmenting TV news into stories. The segmentation of the video stream into stories is achieved by detecting anchor person shots and the text stream is segmented into stories using a Latent Dirichlet Allocation (LDA) based approach. The benefit of the proposed LDA based approach is that along with the story segmentation it also provides the topic distribution associated with each segment. We evaluated our techniques on the TRECVid 2003 benchmark database and found that though the individual systems give comparable results, a combination of the outputs of the two systems gives a significant improvement over the performance of the individual systems.