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Document Cohesion Flow: Striving towards Coherence

Authors :
Crossley, Scott A.
Crossley, Scott A.
Dascalu, Mihai
Trausan-Matu, Stefan
Allen, Laura K.
McNamara, Danielle S.
Crossley, Scott A.
Crossley, Scott A.
Dascalu, Mihai
Trausan-Matu, Stefan
Allen, Laura K.
McNamara, Danielle S.
Source :
Proceedings of the Annual Meeting of the Cognitive Science Society; vol 38, iss 0
Publication Year :
2016

Abstract

Text cohesion is an important element of discourseprocessing. This paper presents a new approach to modeling,quantifying, and visualizing text cohesion using automatedcohesion flow indices that capture semantic links amongparagraphs. Cohesion flow is calculated by applyingCohesion Network Analysis, a combination of semanticdistances, Latent Semantic Analysis, and Latent DirichletAllocation, as well as Social Network Analysis. Experimentsperformed on 315 timed essays indicated that cohesion flowindices are significantly correlated with human ratings of textcoherence and essay quality. Visualizations of the globalcohesion indices are also included to support a more facileunderstanding of how cohesion flow impacts coherence interms of semantic dependencies between paragraphs.

Details

Database :
OAIster
Journal :
Proceedings of the Annual Meeting of the Cognitive Science Society; vol 38, iss 0
Notes :
application/pdf, Proceedings of the Annual Meeting of the Cognitive Science Society vol 38, iss 0
Publication Type :
Electronic Resource
Accession number :
edsoai.on1449587512
Document Type :
Electronic Resource