Abstract
Dividing coherent text into a sequence of coherent segments is a challenging task since different topics/subtopics are often related to a common theme(s). Based on lexical cohesion, we can keep track of words and their repetitions and break text into segments at points where the lexical chains are weak. However, there exist words that are more or less evenly distributed across a document (called document-dependent or distributional stopwords), making it difficult to separate one segment from another. To minimize the overlaps between segments, we propose two new measures for removing distributional stopwords based on word distribution. Our experimental results show that the new measures are both efficient to compute and effective for improving the segmentation performance of expository text and transcribed lecture text.
Access this chapter
Tax calculation will be finalised at checkout
Purchases are for personal use only
Preview
Unable to display preview. Download preview PDF.
References
Beeferman, D., Berger, A., Lafferty, J.D.: Statistical Models for Text Segmentation. Machine Learning 34(1-3), 177–210 (1999)
Choi, F.Y.Y.: Advances in Domain Independent Linear Text Segmentation. In: Proceedings of the NAACL 2000, pp. 26–33 (2000)
Dais, G., Alves, E.: Discovering Topic Boundaries for Text Summarization Based on Word Co-occurrence. In: Proceedings of the RANLP (2005)
Michael, A.K., Halliday, M.A.K., Hasan, R.: Cohesion in English. Longman, New York (1976)
Hearst, M.: Multi-Paragraph Segmentation of Expository Text. In: Proceedings of the ACL, pp. 9–16 (1994)
Heinonen, O.: Optimal Multi-Paragraph Text Segmentation by Dynamic Programming. In: proceedings of the COLING-ACL (1998)
Ji, X., Zha, A.: Domain-independent Text Segmentation Using Anisotropic Diffusion and Dynamic Programming. In: Proceedings of the ACM SIGIR, pp. 322–329 (2003)
Malioutov, I., Barzily, R.: Minimum Cut Model for Spoken Lecture Segmentation (2006)
Jeffery, C., Reynar, J.C.: Topic Segmentation: Algorithms and Application. Ph.D. Thesis, University of Pennsylvania (1998)
Skorochod’ko, E.F.: Adaptive method of automatic abstracting and indexing. In: Proceedings of the IFIP, vol. 71, pp. 1179–1182 (1972)
Utiyama, M., Isahara, H.: A Statistical Model for Domain-Independent Text Segmentation. In: Proceeedings of the ACL, pp. 491–498 (2001)
Youmans, G.: Measuring Lexical Style and Competence: The Type-Token Vocabulary Curve. Style 24, 584–599 (1990)
Youmans, G.: A new Tool for Discourse analysis: The Vocabulary-Management Profile. Language 67(4), 763–789 (1991)
Author information
Authors and Affiliations
Editor information
Rights and permissions
Copyright information
© 2007 Springer-Verlag Berlin Heidelberg
About this paper
Cite this paper
Vasak, J., Song, F. (2007). Word Distribution Based Methods for Minimizing Segment Overlaps. In: Matoušek, V., Mautner, P. (eds) Text, Speech and Dialogue. TSD 2007. Lecture Notes in Computer Science(), vol 4629. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-540-74628-7_21
Download citation
DOI: https://doi.org/10.1007/978-3-540-74628-7_21
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-74627-0
Online ISBN: 978-3-540-74628-7
eBook Packages: Computer ScienceComputer Science (R0)