Document Cohesion Flow: Striving towards Coherence


Autoria(s): Crossley, Scott; Dascalu, Mihai; Trausan-Matu, Stefan; Allen, Laura; McNamara, Danielle
Data(s)

18/08/2016

18/08/2016

01/08/2016

Resumo

Text cohesion is an important element of discourse processing. This paper presents a new approach to modeling, quantifying, and visualizing text cohesion using automated cohesion flow indices that capture semantic links among paragraphs. Cohesion flow is calculated by applying Cohesion Network Analysis, a combination of semantic distances, Latent Semantic Analysis, and Latent Dirichlet Allocation, as well as Social Network Analysis. Experiments performed on 315 timed essays indicated that cohesion flow indices are significantly correlated with human ratings of text coherence and essay quality. Visualizations of the global cohesion indices are also included to support a more facile understanding of how cohesion flow impacts coherence in terms of semantic dependencies between paragraphs.

This study is part of the RAGE project. The RAGE project has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement No 644187. This publication reflects only the author's view. The European Commission is not responsible for any use that may be made of the information it contains.

Identificador

Crossley, S. A., Dascalu, M., Trausan-Matu, S., Allen, L., & McNamara, D. S. (2016). Document Cohesion Flow: Striving towards Coherence. In 38th Annual Meeting of the Cognitive Science Society (pp. 764–769). Philadelphia, PA: Cognitive Science Society.

http://hdl.handle.net/1820/6988

Publicador

Cognitive Science Society

Relação

info:eu-repo/grantAgreement/EC/H2020/644187/EU/Realising an Applied Gaming Eco-system/RAGE

Direitos

openAccess

Palavras-Chave #Cohesion Flow #Natural Language Processing #Computational Models #Cohesion Network Analysis #Coherence #Writing Quality
Tipo

article