Automatic text processing: the transformation, analysis, and retrieval of information by computer
Automatic text processing: the transformation, analysis, and retrieval of information by computer
Introduction to algorithms
Passage-level evidence in document retrieval
SIGIR '94 Proceedings of the 17th annual international ACM SIGIR conference on Research and development in information retrieval
Lexical cohesion computed by thesaural relations as an indicator of the structure of text
Computational Linguistics
TextTiling: segmenting text into multi-paragraph subtopic passages
Computational Linguistics
Text segmentation based on similarity between words
ACL '93 Proceedings of the 31st annual meeting on Association for Computational Linguistics
Multi-paragraph segmentation of expository text
ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
A critique and improvement of an evaluation metric for text segmentation
Computational Linguistics
Text Segmentation into Paragraphs Based on Local Text Cohesion
TSD '01 Proceedings of the 4th International Conference on Text, Speech and Dialogue
Domain-independent text segmentation using anisotropic diffusion and dynamic programming
Proceedings of the 26th annual international ACM SIGIR conference on Research and development in informaion retrieval
Advances in domain independent linear text segmentation
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
A Dynamic Programming Algorithm for Linear Text Segmentation
Journal of Intelligent Information Systems
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
A statistical model for domain-independent text segmentation
ACL '01 Proceedings of the 39th Annual Meeting on Association for Computational Linguistics
Question-driven segmentation of lecture speech text: Towards intelligent e-learning systems
Journal of the American Society for Information Science and Technology
Hierarchical text segmentation from multi-scale lexical cohesion
NAACL '09 Proceedings of Human Language Technologies: The 2009 Annual Conference of the North American Chapter of the Association for Computational Linguistics
Efficient linear text segmentation based on information retrieval techniques
Proceedings of the International Conference on Management of Emergent Digital EcoSystems
Word distribution based methods for minimizing segment overlaps
TSD'07 Proceedings of the 10th international conference on Text, speech and dialogue
TextLec: a novel method of segmentation by topic using lower windows and lexical cohesion
CIARP'07 Proceedings of the Congress on pattern recognition 12th Iberoamerican conference on Progress in pattern recognition, image analysis and applications
A dynamic programming model for text segmentation based on min-max similarity
AIRS'08 Proceedings of the 4th Asia information retrieval conference on Information retrieval technology
Text segmentation by clustering cohesion
CIARP'10 Proceedings of the 15th Iberoamerican congress conference on Progress in pattern recognition, image analysis, computer vision, and applications
New approach for collecting high quality parallel corpora from multilingual websites
Proceedings of the 13th International Conference on Information Integration and Web-based Applications and Services
Using multiple discriminant analysis approach for linear text segmentation
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
Integrated Computer-Aided Engineering
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There exist several methods of calculating a similarity curve, or a sequence of similarity values, representing the lexical cohesion of successive text constituents, e.g., paragraphs. Methods for deciding the locations of fragment boundaries are, however, scarce. We propose a fragmentation method based on dynamic programming. The method is theoretically sound and guaranteed to provide an optimal splitting on the basis of a similarity curve, a preferred fragment length, and a cost function defined. The method is especially useful when control on fragment size is of importance.