Segmentation of Expository Texts by Hierarchical Agglomerative Clustering

We propose a method for segmentation of expository texts based on hierarchical agglomerative clustering. The method uses paragraphs as the basic segments for identifying hierarchical discourse structure in the text, applying lexical similarity between them as the proximity test. Linear segmentation can be induced from the identified structure through application of two simple rules. However the hierarchy can be used also for intelligent exploration of the text. The proposed segmentation algorithm is evaluated against an accepted linear segmentation method and shows comparable results.

• Publication year

  1997

• Venue

  arXiv.org

• Publication date

  1997-09-26

• Fields of study

  Linguistics, Computer Science

• Identifiers
  arXiv cmp-lg/9709015
• External record

  Open on Semantic Scholar

• Source metadata

  Semantic Scholar

• No claims are published for this paper.

• No concepts are published for this paper.

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