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Lexical cohesion computed by thesaural relations as an indicator of the structure of text
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Topic-based document segmentation with probabilistic latent semantic analysis
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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
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Topic analysis using a finite mixture model
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TextTiling: segmenting text into multi-paragraph subtopic passages
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How to thematically segment texts by using lexical cohesion?
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Optimal multi-paragraph text segmentation by dynamic programming
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Thematic segmentation of texts: two methods for two kinds of texts
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Text segmentation using reiteration and collocation
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ACL '94 Proceedings of the 32nd annual meeting on Association for Computational Linguistics
Word sense disambiguation and text segmentation based on lexical cohesion
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ACL '03 Proceedings of the 41st Annual Meeting on Association for Computational Linguistics - Volume 1
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HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
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Applied Artificial Intelligence
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AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 2
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This paper proposes a new indicator of text structure, called the lexical cohesion profile (LCP), which locates segment boundaries in a text. A text segment is a coherent scene; the words in a segment are linked together via lexical cohesion relations. LCP records mutual similarity of words in a sequence of text. The similarity of words, which represents their cohesiveness, is computed using a semantic network. Comparison with the text segments marked by a number of subjects shows that LCP closely correlates with the human judgments. LCP may provide valuable information for resolving anaphora and ellipsis.