Leveraging Lexical Cohesion and Disruption for Topic Segmentation

A probabilistic segment model combining lexical cohesion and disruption for topic segmentation (Un mod\`ele segmental probabiliste combinant coh\'esion lexicale et rupture lexicale pour la segmentation th\'ematique) [in French]

BeamSeg: A Joint Model for Multi-Document Segmentation and Topic Identification

We propose BeamSeg, a joint model for segmentation and topic identification of documents from the same domain. The model assumes that lexical cohesion can be observed across documents, meaning that segments describing th…

Hrebs and Cohesion Chains as similar tools for semantic text properties research

In this study it is proven that the Hrebs used in Denotation analysis of texts and Cohesion Chains (defined as a fusion between Lexical Chains and Coreference Chains) represent similar linguistic tools. This result gives…

`Keep it Together': Enforcing Cohesion in Extractive Summaries by Simulating Human Memory

Extractive summaries are usually presented as lists of sentences with no expected cohesion between them. In this paper, we aim to enforce cohesion whilst controlling for informativeness and redundancy in summaries, in ca…

OntoSeg: a Novel Approach to Text Segmentation using Ontological Similarity

Text segmentation (TS) aims at dividing long text into coherent segments which reflect the subtopic structure of the text. It is beneficial to many natural language processing tasks, such as Information Retrieval (IR) an…