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Assessment of text coherence using an ontology‐based relatedness measurement method
Author(s) -
Giray Görkem,
Ünalır Murat Osman
Publication year - 2020
Publication title -
expert systems
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.365
H-Index - 38
eISSN - 1468-0394
pISSN - 0266-4720
DOI - 10.1111/exsy.12505
Subject(s) - computer science , coherence (philosophical gambling strategy) , ontology , inference , representation (politics) , natural language processing , variety (cybernetics) , information retrieval , artificial intelligence , statistics , mathematics , philosophy , epistemology , politics , political science , law
This paper proposes a novel method for assessing text coherence. Central to this approach is an ontology‐based representation of text, which captures the level of relatedness between consecutive sentences via ontologies. Our method encompasses annotating text using ontological concepts and assessing text coherence based on relatedness measurement among these concepts. The ontology‐based relatedness measurement method used in this study considers various types of relationships in ontologies and derived relationships via an inference engine for computing relatedness. We hypothesized that rich variety of relationships and inferred facts in ontologies would improve the success of text coherence assessment. Our results demonstrate that the use of ontologies yields to coherence values that have a higher correlation with human ratings.