Results 61 to 70 of about 15,278 (236)
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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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
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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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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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Large-Scale Goodness Polarity Lexicons for Community Question Answering
, 2017 We transfer a key idea from the field of sentiment analysis to a new domain: community question answering (cQA). The cQA task we are interested in is the following: given a question and a thread of comments, we want to re-rank the comments so that the ...
Church Kenneth Ward +5 more
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HHMM at SemEval-2019 Task 2: Unsupervised Frame Induction using Contextualized Word Embeddings
, 2019 We present our system for semantic frame induction that showed the best performance in Subtask B.1 and finished as the runner-up in Subtask A of the SemEval 2019 Task 2 on unsupervised semantic frame induction (QasemiZadeh et al., 2019).
Anwar, Saba +5 more
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Extracting knowledge from customer reviews: an integrated framework for digital platform analytics
International Transactions in Operational Research, Volume 32, Issue 4, Page 2061-2086, July 2025.Abstract Online review sites play a crucial role in shaping consumer purchasing decisions, making the analysis of customer feedback essential for businesses. Given the complexity of these reviews, often including both quantitative and qualitative data, advanced analytical frameworks are necessary.
Anastasios Kyriakidis +1 more
wiley +1 more source
SemEval-2017 Task 12: Clinical TempEval [PDF]
Proceedings of the 11th International Workshop on Semantic Evaluation
(SemEval-2017), 2017 Clinical TempEval 2017 aimed to answer the question: how well do systems trained on annotated timelines for one medical condition (colon cancer) perform in predicting timelines on another medical condition (brain cancer)? Nine sub-tasks were included, covering problems in time expression identification, event expression identification and temporal ...
Guergana Savova +3 more
openaire +2 more sources
A New Sentiment-Enhanced Word Embedding Method for Sentiment Analysis
Applied Sciences, 2022 Since some sentiment words have similar syntactic and semantic features in the corpus, existing pre-trained word embeddings always perform poorly in sentiment analysis tasks.
Qizhi Li +4 more
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