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What a transparent Romance language with a Germanic gender-determiner mapping tells us about gender retrieval: Insights from European Portuguese ; Gender processing in European Portuguese
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The role of object novelty and pragmatic reasoning in referent selection and word learning (Study 2b) ...
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Experts' Selection for Neutrosophic Delphi Method. A Case Study of Hotel Activity ...
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Experts' Selection for Neutrosophic Delphi Method. A Case Study of Hotel Activity ...
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A New Ontology-Based Method for Arabic Sentiment Analysis
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In: Big Data and Cognitive Computing; Volume 6; Issue 2; Pages: 48 (2022)
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Abstract:
Arabic sentiment analysis is a process that aims to extract the subjective opinions of different users about different subjects since these opinions and sentiments are used to recognize their perspectives and judgments in a particular domain. Few research studies addressed semantic-oriented approaches for Arabic sentiment analysis based on domain ontologies and features’ importance. In this paper, we built a semantic orientation approach for calculating overall polarity from the Arabic subjective texts based on built domain ontology and the available sentiment lexicon. We used the ontology concepts to extract and weight the semantic domain features by considering their levels in the ontology tree and their frequencies in the dataset to compute the overall polarity of a given textual review based on the importance of each domain feature. For evaluation, an Arabic dataset from the hotels’ domain was selected to build the domain ontology and to test the proposed approach. The overall accuracy and f-measure reach 79.20% and 78.75%, respectively. Results showed that the approach outperformed the other semantic orientation approaches, and it is an appealing approach to be used for Arabic sentiment analysis.
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Keyword:
arabic language; domain features; domain ontology; feature level sentiment analysis; features selection and weighting; semantic orientation; sentiment analysis
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URL: https://doi.org/10.3390/bdcc6020048
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A Dynamic Attention and Multi-Strategy-Matching Neural Network Based on Bert for Chinese Rice-Related Answer Selection
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In: Agriculture; Volume 12; Issue 2; Pages: 176 (2022)
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Information Processing by Selective Machines
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In: Proceedings; Volume 81; Issue 1; Pages: 122 (2022)
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Adapting Fleming-Type Learning Style Classifications to Deaf Student Behavior
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In: Sustainability; Volume 14; Issue 8; Pages: 4799 (2022)
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Integrating Triple Bottom Line in Sustainable Chemical Supplier Selection: A Compromise Decision-Making-Based Spherical Fuzzy Approach
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In: Processes; Volume 10; Issue 5; Pages: 889 (2022)
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A Supplier Selection Model Using Alternative Ranking Process by Alternatives’ Stability Scores and the Grey Equilibrium Product
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In: Processes; Volume 10; Issue 5; Pages: 917 (2022)
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Selecting for Learning Potential: Is Implicit Learning the New Cognitive Ability?
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In: Journal of Intelligence; Volume 10; Issue 2; Pages: 24 (2022)
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The persistence and evolutionary consequences of vestigial behaviours
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Auxiliary selection is Agree : Person-driven and argument-structure-based splits
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Aplicaciones de la disponibilidad léxica a la lexicografía de aprendizaje en ELE ; Applications of lexical availability in lexicography intended for learners of Spanish as a foreign language
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Transformative Vocabulary: Fusing Vocabulary Instruction with Citizenship Education
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In: Certificate of Advanced Studies (CAS) in Literacy (2022)
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Сбои лексического выбора у дошкольников ; Speech Mechanisms of Lexical Mischoices in Reschoolers’ Narratives
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Community diversity determines the evolution of synthetic bacterial communities under artificial selection
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In: https://hal-agrosup-dijon.archives-ouvertes.fr/hal-03378428 ; 2021 (2021)
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When Do Opposites Attract? A Model Uncovering the Evolution of Disassortative Mating
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In: ISSN: 0003-0147 ; EISSN: 1537-5323 ; American Naturalist ; https://hal.archives-ouvertes.fr/hal-03375720 ; American Naturalist, University of Chicago Press, 2021, pp.000-000. ⟨10.1086/716509⟩ (2021)
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Hubs and clusters approach to unlock the development of carbon capture and storage – Case study in Spain
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