Article
Version 1
Preserved in Portico This version is not peer-reviewed
DASTEX: a New Readability Formula based on Semantic Complexity of Text
Version 1
: Received: 22 March 2021 / Approved: 24 March 2021 / Online: 24 March 2021 (12:58:11 CET)
Version 2 : Received: 4 September 2021 / Approved: 6 September 2021 / Online: 6 September 2021 (13:33:34 CEST)
Version 2 : Received: 4 September 2021 / Approved: 6 September 2021 / Online: 6 September 2021 (13:33:34 CEST)
How to cite: Besharati, M. R.; Izadi, M. DASTEX: a New Readability Formula based on Semantic Complexity of Text. Preprints 2021, 2021030582. https://doi.org/10.20944/preprints202103.0582.v1 Besharati, M. R.; Izadi, M. DASTEX: a New Readability Formula based on Semantic Complexity of Text. Preprints 2021, 2021030582. https://doi.org/10.20944/preprints202103.0582.v1
Abstract
Simple measures often couldn’t count a deep complexity. In the case of semantic complexity of the text, conventional readability formulas share a common style, a common sort of achievements and a common borders of limitation: These formulas lack a semantics-aware approach and as a result, a precise measurement of semantic complexity couldn’t be done by them. In this paper, we introduce DASTEX, a novel semantics-aware complexity measure for semantic complexity of text. By DASTEX, a new layer of complexity analysis are opened for NLP, cognitive and computational tasks. This measure benefits from an intuitionistic underlying formal model which consider semantic as a lattice of intuitions. This yields to a well-defined definition for semantic of a text and its complexity. DASTEX is a practical analysis method upon this formal model. So a complete suite of idea, model and method are prepared to result in a simple but yet deep measure for semantic complexity of text. The evaluation of the proposed approach is done by a detailed example, a case study, a set of eighteen human-judgment experiments and a corpus-based evaluation. The results show that DASTEX is capable of measuring the semantic complexity of text. The Experiment-results demonstrate that our method consistently outperforms the random baseline in terms of better precision and accuracy.
Keywords
Semantic Complexity; Semantics; Text Complexity; Readability Formulae
Subject
Computer Science and Mathematics, Algebra and Number Theory
Copyright: This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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