Results 31 to 40 of about 13,354 (114)
Ensemble BiLSTM: A Novel Approach for Aspect Extraction From Online Text
IEEE AccessAspect extraction poses a significant challenge in Natural Language Processing (NLP). Extracting explicit and implicit aspects from online text data remains an ongoing challenge despite significant research efforts.
Mikail Muhammad Azman Busst +4 more
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Duluth at SemEval-2017 Task 6: Language Models in Humor Detection
, 2017 This paper describes the Duluth system that participated in SemEval-2017 Task 6 #HashtagWars: Learning a Sense of Humor. The system participated in Subtasks A and B using N-gram language models, ranking highly in the task evaluation. This paper discusses
Pedersen, Ted, Yan, Xinru
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SemEval-2016 Task 13: Taxonomy Extraction Evaluation (TExEval-2) [PDF]
, 2016 This paper describes the second edition of the shared task on Taxonomy Extraction Evaluation organised as part of SemEval 2016. This task aims to extract hypernym-hyponym relations between a given list of domain-specific terms and then to construct a ...
Bordea, Georgeta +2 more
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Multi-Head Self-Attention Gated-Dilated Convolutional Neural Network for Word Sense Disambiguation
IEEE Access, 2023 Word sense disambiguation (WSD) is to determine correct sense of ambiguous word based on its context. WSD is widely used in text classification, machine translation and information retrieval and so on.
Chun-Xiang Zhang +2 more
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Complex Word Identification: Challenges in Data Annotation and System Performance
, 2017 This paper revisits the problem of complex word identification (CWI) following up the SemEval CWI shared task. We use ensemble classifiers to investigate how well computational methods can discriminate between complex and non-complex words.
Malmasi, Shervin +3 more
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Employing synthetic data for addressing the class imbalance in aspect-based sentiment classification
Journal of Information and TelecommunicationThe class imbalance problem, in which the distribution of different classes in training data is unequal or skewed, is a prevailing problem. This can lead to classifier algorithms being biased, negatively impacting the performance of the minority class ...
Vaishali Ganganwar, Ratnavel Rajalakshmi
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Automatic Accuracy Prediction for AMR Parsing
, 2019 Meaning Representation (AMR) represents sentences as directed, acyclic and rooted graphs, aiming at capturing their meaning in a machine readable format. AMR parsing converts natural language sentences into such graphs.
Frank, Anette, Opitz, Juri
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, 2017 We present our submitted systems for Semantic Textual Similarity (STS) Track 4 at SemEval-2017. Given a pair of Spanish-English sentences, each system must estimate their semantic similarity by a score between 0 and 5.
Agnes, Frederic +3 more
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, 2018 We describe our system for SemEval-2018 Shared Task on Semantic Relation Extraction and Classification in Scientific Papers where we focus on the Classification task.
Dhyani, Dushyanta
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IEEE Access, 2023 With the expansion of social networks, sentiment analysis has become one of the hot topics in machine learning. However, in traditional sentiment analysis, the text is considered of a general nature and ignores the different aspects that may exist in the
Kia Jahanbin, Mohammad Ali Zare Chahooki
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