Results 1 to 10 of about 21,648 (265)
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
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
doaj +1 more source
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
core +1 more source
Combining Sentiment Lexica with a Multi-View Variational Autoencoder [PDF]
, 2019 When assigning quantitative labels to a dataset, different methodologies may rely on different scales. In particular, when assigning polarities to words in a sentiment lexicon, annotators may use binary, categorical, or continuous labels.
Augenstein, Isabelle +4 more
core +2 more sources
, 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
core +1 more source
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
doaj +1 more source
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
doaj +1 more source
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
core +1 more source
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
core +1 more source
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
doaj +1 more source