Results 141 to 150 of about 15,951 (231)
CSReader at SemEval-2018 Task 11: Multiple Choice Question Answering as Textual Entailment [PDF]
, 2018 Zhengping Jiang, Qi Sun
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Breaking Sticks and Ambiguities with Adaptive Skip-gram
, 2015 Recently proposed Skip-gram model is a powerful method for learning high-dimensional word representations that capture rich semantic relationships between words. However, Skip-gram as well as most prior work on learning word representations does not take
Bartunov, Sergey +3 more
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HR@JUST Team at SemEval-2020 Task 4: The Impact of RoBERTa Transformer for Evaluation Common Sense Understanding [PDF]
, 2020 Heba Al-Jarrah +2 more
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Explainable Aspect-Based Sentiment Analysis Using Transformer Models
Big Data and Cognitive ComputingAn aspect-based sentiment analysis (ABSA) aims to perform a fine-grained analysis of text to identify sentiments and opinions associated with specific aspects.
Isidoros Perikos +1 more
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Identifying interactions between chemical entities in biomedical text
Journal of Integrative Bioinformatics, 2014 Interactions between chemical compounds described in biomedical text can be of great importance to drug discovery and design, as well as pharmacovigilance.
Lamurias Andre +2 more
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CLEARumor at SemEval-2019 Task 7: ConvoLving ELMo Against Rumors [PDF]
, 2019 Ipek Baris +2 more
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Extracting Explicit and Implicit Aspects Using Deep Learning
Emerging Science JournalThe proliferation of user-generated content on social networks and websites has heightened the significance of sentiment analysis, also known as opinion mining, as a critical tool for comprehending people’s attitudes toward various topics.
Mikail Muhammad Azman Busst +3 more
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Graph-Based Complex Representation in Inter-Sentence Relation Recognition in Polish Texts
Cybernetics and Information Technologies, 2018 This paper presents a supervised approach to the recognition of Cross-document Structure Theory (CST) relations in Polish texts. Its core is a graph-based representation constructed for sentences.
Janz Arkadiusz +2 more
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Twitter Sentiment Classification Method Based on Convolutional Neutral Network and Multi-feature Fusion [PDF]
Jisuanji gongcheng, 2018 In order to classify the emotion for users expressions and comments on social networks,this paper presents a sentiment classification method which combines Convolutional Neural Network(CNN) and multi-feature fusion.It designs corpus features and lexicon ...
WANG Rujiao,JI Donghong
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IEEE AccessAspect extraction is the most important factor influencing the quality of Aspect-Based Sentiment Analysis (ABSA). Aspect extractions are divided into three approaches: supervised, unsupervised, and hybrid methods.
Mohammad Mashrekul Kabir +2 more
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