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All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year AND OR AND NOT All fields Title Creator / Publisher Keyword Year Sort by creator [A → Z]' creator [Z → A]' publishing year ↑ (asc)' publishing year ↓ (desc)' title [A → Z]' title [Z → A]' Simple Search Hits 1 – 6 of 6 1 LUX (Linguistic aspects Under eXamination): Discourse Analysis for Automatic Fake News Classification ... The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing 2021; Azevedo, Lucas; d'Aquin, Mathieu. - : Underline Science Inc., 2021 BASE Show details 2 Towards the Prediction of Semantic Complexity Based on Concept Graphs ; Vers la prédiction de complexité sémantique fondée sur les graphes de concepts Venant, Rémi; D'Aquin, Mathieu In: 12th International Conference on Educational Data Mining (EDM 2019) ; https://hal.archives-ouvertes.fr/hal-02315319 ; 12th International Conference on Educational Data Mining (EDM 2019), Jul 2019, Montreal, Canada. pp.188-197 ; educationaldatamining.org/EDM2019/ (2019) Abstract: International audience ; The evaluation of text complexity is an important topic in education. While this objective has been addressed by approaches using lexical and syntactic analysis for decades, semantic complexity is less common, and the recent research works that tackle this question rely on machine learning algorithms that are hardly explainable and are not specifically designed to measure this variable. To address this issue, we explore in this paper the engineering of novel features to evaluate conceptual complexity. Through the construction of a knowledge graph that captures the concepts present in a text and their generalized forms, we measure different graph-based metrics to express such a complexity. Eventually , early-stage evaluations based on a well-known public corpus of students' productions show that the use of these metrics significantly improves performance compared to a state-of-the-art binary neural network classifier. Keyword: [INFO.EIAH]Computer Science [cs]/Technology for Human Learning; [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; [INFO.INFO-NE]Computer Science [cs]/Neural and Evolutionary Computing [cs.NE]; [INFO.INFO-TT]Computer Science [cs]/Document and Text Processing; concept complexity; features engineering; knowledge graph; machine learning; neural network; semantic complexity URL: https://hal.archives-ouvertes.fr/hal-02315319 https://hal.archives-ouvertes.fr/hal-02315319/file/25_paper_154.pdf https://hal.archives-ouvertes.fr/hal-02315319/document BASE Hide details 3 SPARQL query verbalization for explaining semantic search engine queries Ell, Basil; Harth, Andreas; Simperl, Elena. - : Springer International Publishing, 2014 BASE Show details 4 Ontology evolution: a process-centric survey Fouad, Zablith; Antoniou, Grigoris; D'Aquin, Mathieu. - : Cambridge, 2013 BASE Show details 5 DOOR: towards a formalization of ontology relations Allocca, Carlo; d'Aquin, Mathieu; Motta, Enrico. - 2009 BASE Show details 6 Towards a Semantic Portal for Oncology using a Description Logic with Fuzzy Concrete Domains D'Aquin, Mathieu; Lieber, Jean; Napoli, Amedeo In: Fuzzy Logic and the Semantic Web ; https://hal.inria.fr/inria-00001254 ; Elie Sanchez. Fuzzy Logic and the Semantic Web, 1 (1), Elsevier, 2006, Capturing intelligence, 0-444-51948-3 (2006) BASE Show details

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