CoCo: A tool for automatically assessing conceptual complexity of texts

Štajner, Sanja ; Nisioi, Sergiu ; Hulpus, Ioana

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URL:	https://madoc.bib.uni-mannheim.de/55731
Additional URL:	https://www.aclweb.org/anthology/2020.lrec-1.887
URN:	urn:nbn:de:bsz:180-madoc-557312
Document Type:	Conference or workshop publication
Year of publication:	2020
Book title:	LREC 2020 Marseille : Twelfth International Conference on Language Resources and Evaluation : May 11-16, 2020, Palais du Pharo, Marseille, France : conference proceedings
Page range:	7179-7186
Conference title:	LREC 2020 (conference canceled)
Location of the conference venue:	Marseille, France
Date of the conference:	canceled
Publisher:	Calzolari, Nicoletta
Place of publication:	Paris
Publishing house:	European Language Resources Association
ISBN:	979-10-95546-34-4
Related URLs:	https://lrec2020.lrec-conf.org/en/
Publication language:	English
Institution:	School of Business Informatics and Mathematics > Practical Computer Science II: Artificial Intelligence (Stuckenschmidt 2009-)
Pre-existing license:	Creative Commons Attribution, Non-Commercial 4.0 International (CC BY-NC 4.0)
Subject:	020 Library and information sciences
Abstract:	Traditional text complexity assessment usually takes into account only syntactic and lexical text complexity. The task of automatic assessment of conceptual text complexity, important for maintaining reader's interest and text adaptation for struggling readers, has only been proposed recently. In this paper, we present CoCo - a tool for automatic assessment of conceptual text complexity, based on using the current state-of-the-art unsupervised approach. We make the code and API freely available for research purposes, and describe the code and the possibility for its personalization and adaptation in details. We compare the current implementation with the state of the art, discussing the influence of the choice of entity linker on the performances of the tool. Finally, we present results obtained on two widely used text simplification corpora, discussing the full potential of the tool.