Algorithms for clustering data
Algorithms for clustering data
A Validity Measure for Fuzzy Clustering
IEEE Transactions on Pattern Analysis and Machine Intelligence
Automatic text decomposition using text segments and text themes
Proceedings of the the seventh ACM conference on Hypertext
Statistical Models for Text Segmentation
Machine Learning - Special issue on natural language learning
A critique and improvement of an evaluation metric for text segmentation
Computational Linguistics
Thematic alignment of recorded speech with documents
Proceedings of the 2003 ACM symposium on Document engineering
Xed: A New Tool for eXtracting Hidden Structures from Electronic Documents
DIAL '04 Proceedings of the First International Workshop on Document Image Analysis for Libraries (DIAL'04)
Thematic segmentation of texts: two methods for two kinds of texts
COLING '98 Proceedings of the 17th international conference on Computational linguistics - Volume 1
Multi-paragraph segmentation of expository text
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Algorithmic Graph Theory and Perfect Graphs (Annals of Discrete Mathematics, Vol 57)
Thematic segmentation of meetings through document/speech alignment
Proceedings of the 12th annual ACM international conference on Multimedia
Linear text segmentation using a dynamic programming algorithm
EACL '03 Proceedings of the tenth conference on European chapter of the Association for Computational Linguistics - Volume 1
Documenting the pen-based interaction
WebMedia '05 Proceedings of the 11th Brazilian Symposium on Multimedia and the web
SlideSeer: a digital library of aligned document and presentation pairs
Proceedings of the 7th ACM/IEEE-CS joint conference on Digital libraries
Detection and resolution of references to meeting documents
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
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In this paper, we describe a new method for a simultaneous thematic segmentation of the meeting dialogs and the documents discussed or visible throughout the meeting. This bi-modal method is suitable for multimodal applications that are centered on documents, such as meetings and lectures, where documents can be aligned with meeting dialogs. Bringing into play this alignment, our bi-modal segmentation method first transforms its results into a set of nodes in a 2D graph space, where the two axes represent respectively the document units and the meeting dialogs units. Secondly, via a clustering method, the most connected regions in the constituted bi-graph are detected. Finally, the denser clusters are projected on the two axes. The two sequences of segments, obtained on both axes, represent the thematic structure of the document and of the meeting dialogs respectively. We present in this article this bi-modal segmentation technique and its performance compared with two mono-modal segmentation methods.