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Knowledge Representation and Reasoning with an Extended Dynamic Uncertain Causality Graph under the Pythagorean Uncertain Linguistic Environment
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In: Applied Sciences; Volume 12; Issue 9; Pages: 4670 (2022)
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Using Peircean Semiotics as the Grounding of Cognition
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In: Proceedings; Volume 81; Issue 1; Pages: 135 (2022)
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Formalization of AMR Inference via Hybrid Logic Tableaux ...
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Ranking Semantics for Argumentation Systems With Necessities
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In: IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence ; https://hal.archives-ouvertes.fr/hal-03002056 ; IJCAI 2020 - 29th International Joint Conference on Artificial Intelligence, Jan 2021, Yokohama / Virtual, Japan. pp.1912-1918, ⟨10.24963/ijcai.2020/265⟩ (2021)
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The contribution of visual articulatory gestures and orthography to speech processing: Evidence from novel word learning
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In: ISSN: 0278-7393 ; EISSN: 1939-1285 ; Journal of Experimental Psychology: Learning, Memory, and Cognition ; https://hal.archives-ouvertes.fr/hal-03189083 ; Journal of Experimental Psychology: Learning, Memory, and Cognition, American Psychological Association, In press, ⟨10.1037/xlm0001036⟩ (2021)
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APiCS-Ligt: Towards Semantic Enrichment of Interlinear Glossed Text ...
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Ionov, Maxim. - : Schloss Dagstuhl - Leibniz-Zentrum für Informatik, 2021
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Essential Features in a Theory of Context for Enabling Artificial General Intelligence
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In: Applied Sciences; Volume 11; Issue 24; Pages: 11991 (2021)
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Enriching Word Embeddings with Food Knowledge for Ingredient Retrieval ...
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An Ontology for CoNLL-RDF: Formal Data Structures for TSV Formats in Language Technology ...
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Semantic Description of Plant Phenological Development Stages, starting with Grapevine
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In: ISSN: 1865-0929 ; Communications in Computer and Information Science ; Communications in Computer and Information Science (CCIS) ; 14th international conference on Metadata and Semantics Research Conference (MTSR) ; https://hal.archives-ouvertes.fr/hal-02996846 ; 14th international conference on Metadata and Semantics Research Conference (MTSR), Dec 2020, Madrid, Spain. pp.257-268, ⟨10.1007/978-3-030-71903-6_25⟩ ; http://www.mtsr-conf.org/home (2020)
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Strengths of Fuzzy Techniques in Data Science
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In: Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications ; https://hal.sorbonne-universite.fr/hal-01676195 ; Kosheleva, O.; Shary, S.P.; Xiang, G.; Zapatrin, R. Beyond Traditional Probabilistic Data Processing Techniques: Interval, Fuzzy, etc. Methods and Their Applications, 835, Springer, pp.111-119, 2020, Studies in Computational Intelligence, 978-3-030-31041-7. ⟨10.1007/978-3-030-31041-7_6⟩ (2020)
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Abstract:
International audience ; We show that many existing fuzzy methods for machine learning and data mining contribute to providing solutions to data science challenges, even though statistical approaches are often presented as major tools to cope with big data and modern user expectations of their exploitation. The multiple capacities of fuzzy and related knowledge representation methods make them inescapable to deal with various types of uncertainty inherent in all kinds of data.
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Keyword:
[INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.4: Knowledge Representation Formalisms and Methods; ACM: I.: Computing Methodologies/I.2: ARTIFICIAL INTELLIGENCE/I.2.6: Learning/I.2.6.4: Knowledge acquisition; Data science; fuzzy knowledge representation; fuzzy technique; linguistic summary; similarity; uncertainty
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URL: https://hal.sorbonne-universite.fr/hal-01676195/file/ArticleVladik2017_3.pdf https://hal.sorbonne-universite.fr/hal-01676195/document https://hal.sorbonne-universite.fr/hal-01676195 https://doi.org/10.1007/978-3-030-31041-7_6
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Reasoning with Ontologies
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In: A Guided Tour of Artificial Intelligence Research ; https://hal-lirmm.ccsd.cnrs.fr/lirmm-02922020 ; A Guided Tour of Artificial Intelligence Research, pp.185-215, 2020, Volume I: Knowledge Representation, Reasoning and Learning, 978-3-030-06163-0. ⟨10.1007/978-3-030-06164-7_6⟩ (2020)
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Defying Wikidata: Validation of terminological relations in the web of data
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Opinion Mining in Higher Education: A Corpus-Based Approach (Supplementary material) ...
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