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Jibes & Delights: A Dataset of Targeted Insults and Compliments to Tackle Online Abuse ...
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ViTA: Visual-Linguistic Translation by Aligning Object Tags ...
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HASOCOne@FIRE-HASOC2020: Using BERT and Multilingual BERT models for Hate Speech Detection ...
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Multilingual Pre-Trained Transformers and Convolutional NN Classification Models for Technical Domain Identification ...
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gundapusunil at SemEval-2020 Task 9: Syntactic Semantic LSTM Architecture for SENTIment Analysis of Code-MIXed Data ...
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A SentiWordNet Strategy for Curriculum Learning in Sentiment Analysis ...
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Word Level Language Identification in English Telugu Code Mixed Data ...
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A Sentiwordnet Strategy for Curriculum Learning in Sentiment Analysis
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In: Natural Language Processing and Information Systems (2020)
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Abstract:
Curriculum Learning (CL) is the idea that learning on a training set sequenced or ordered in a manner where samples range from easy to difficult, results in an increment in performance over otherwise random ordering. The idea parallels cognitive science’s theory of how human brains learn, and that learning a difficult task can be made easier by phrasing it as a sequence of easy to difficult tasks. This idea has gained a lot of traction in machine learning and image processing for a while and recently in Natural Language Processing (NLP). In this paper, we apply the ideas of curriculum learning, driven by SentiWordNet in a sentiment analysis setting. In this setting, given a text segment, our aim is to extract its sentiment or polarity. SentiWordNet is a lexical resource with sentiment polarity annotations. By comparing performance with other curriculum strategies and with no curriculum, the effectiveness of the proposed strategy is presented. Convolutional, Recurrence and Attention based architectures are employed to assess this improvement. The models are evaluated on standard sentiment dataset, Stanford Sentiment Treebank.
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Keyword:
Article
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URL: https://doi.org/10.1007/978-3-030-51310-8_16 http://www.ncbi.nlm.nih.gov/pmc/articles/PMC7298176/
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Conversational implicatures in English dialogue: Annotated dataset ...
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BCSAT : A Benchmark Corpus for Sentiment Analysis in Telugu Using Word-level Annotations ...
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Automatic Target Recovery for Hindi-English Code Mixed Puns ...
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Towards Automation of Sense-type Identification of Verbs in OntoSenseNet(Telugu) ...
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Towards Enhancing Lexical Resource and Using Sense-annotations of OntoSenseNet for Sentiment Analysis ...
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Context and Humor: Understanding Amul advertisements of India ...
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