Results 51 to 60 of about 15,528 (226)
Improving sentiment analysis with learning concepts from concept, patterns lexicons and negations
Ain Shams Engineering Journal, 2022 The way of expressing sentiment (−ve/+ve) in the form of textual information depends on the way of thinking of human beings. Identifying aspect extraction and sentiment polarity from written texts is a crucial task.
Anima Pradhan +2 more
doaj +1 more source
JokeMeter at SemEval-2020 Task 7: Convolutional Humor [PDF]
Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020 This paper describes our system that was designed for Humor evaluation within the SemEval-2020 Task 7. The system is based on convolutional neural network architecture. We investigate the system on the official dataset, and we provide more insight to model itself to see how the learned inner features look.
Martin Docekal +3 more
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The Meaning Factory at SemEval-2017 Task 9: Producing AMRs with Neural Semantic Parsing [PDF]
, 2017 We evaluate a semantic parser based on a character-based sequence-to-sequence model in the context of the SemEval-2017 shared task on semantic parsing for AMRs.
Bos, Johan, van Noord, Rik
core +2 more sources
On SemEval-2010 Japanese WSD Task
Journal of Natural Language Processing, 2011 An overview of the SemEval-2 Japanese WSD task is presented. The new characteristics of our task are (1) the task will use the first balanced Japanese sense-tagged corpus, and (2) the task will take into account not only the instances that have a sense in the given set but also the instances that have a sense that cannot be found in the set.
Manabu Okumura +3 more
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SemEval-2017 Task 3: Community Question Answering [PDF]
Proceedings of the 11th International Workshop on Semantic Evaluation
(SemEval-2017), 2017 We describe SemEval-2017 Task 3 on Community Question Answering. This year, we reran the four subtasks from SemEval-2016:(A) Question-Comment Similarity,(B) Question-Question Similarity,(C) Question-External Comment Similarity, and (D) Rerank the correct answers for a new question in Arabic, providing all the data from 2015 and 2016 for training, and ...
Preslav Nakov +6 more
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Two knowledge-based methods for High-Performance Sense Distribution Learning [PDF]
, 2018 Knowing the correct distribution of senses within a corpus can potentially boost the performance of Word Sense Disambiguation (WSD) systems by many points.
Navigli, Roberto, Pasini, Tommaso
core +1 more source
SemEval-2013 Task 5: Evaluating Phrasal Semantics [PDF]
, 2013 This paper describes the SemEval-2013 Task 5: “Evaluating Phrasal Semantics”. Its first subtask is about computing the semantic similarity of words and compositional phrases of minimal length. The second one addresses deciding the compositionality of phrases in a given context.
Korkontzelos, I +3 more
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SemEval-2020 Task 4: Commonsense Validation and Explanation [PDF]
Proceedings of the Fourteenth Workshop on Semantic Evaluation, 2020 In this paper, we present SemEval-2020 Task 4, Commonsense Validation and Explanation (ComVE), which includes three subtasks, aiming to evaluate whether a system can distinguish a natural language statement that makes sense to humans from one that does not, and provide the reasons.
Yilong Wang +5 more
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A Single Attention-Based Combination of CNN and RNN for Relation Classification
IEEE Access, 2019 As a vital task in natural language processing, relation classification aims to identify relation types between entities from texts. In this paper, we propose a novel Att-RCNN model to extract text features and classify relations by combining recurrent ...
Xiaoyu Guo +4 more
doaj +1 more source
Word Sense Disambiguation Based on RegNet With Efficient Channel Attention and Dilated Convolution
IEEE Access, 2023 Word sense disambiguation (WSD) is one of key problems in field of natural language processing. Ambiguous word often has different meanings in different contexts.
Chun-Xiang Zhang +2 more
doaj +1 more source