Results 41 to 50 of about 17,106 (265)
Lexicon-Enhanced Attention Network Based on Text Representation for Sentiment Classification
Applied Sciences, 2019 Text representation learning is an important but challenging issue for various natural language processing tasks. Recently, deep learning-based representation models have achieved great success for sentiment classification. However, these existing models
Wenkuan Li +5 more
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Sentiment Analysis by Fusing Text and Location Features of Geo-Tagged Tweets
IEEE Access, 2020 Twitter sentiment analysis provides valuable feedback from public emotion concerning certain events or products. Current research has been focused on obtaining sentiment features from vectorized lexical and syntactic feature from tweets, without further ...
Wei Lun Lim +2 more
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Sentiment and Sarcasm Classification With Multitask Learning [PDF]
IEEE Intelligent Systems, 2019 Sentiment classification and sarcasm detection are both important natural language processing (NLP) tasks. Sentiment is always coupled with sarcasm where intensive emotion is expressed. Nevertheless, most literature considers them as two separate tasks.
Navonil Majumder +5 more
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IEEE Access, 2018 Sentiment analysis is an important problem in natural language processing, which plays an important role in many fields, such as information forecasting, knowledge classification, and product review. Because Tibetan microblogs have their own unique form,
Lirong Qiu, Qiao Lei, Zhen Zhang
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Sentiment Classification across Domains [PDF]
, 2009 In this paper we consider the problem of building models that have high sentiment classification accuracy without the aid of a labeled dataset from the target domain. For that purpose, we present and evaluate a novel method based on level of abstraction of nouns. By comparing high-level features (e.g.
Dinko Dimchev Lambov +2 more
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Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Osteosarcoma (OS) and Ewing sarcoma (EWS) are the most common primary bone cancers in children, but acute thrombosis is poorly characterized in this population. Our study evaluated the rates of venous thromboembolism (VTE) and associated risk factors in pediatric patients with bone sarcomas treated over a 10‐year period encompassing
Sarah Kappa +8 more
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A Bibliometric Analysis of Publications in Uremic Toxins From 1991 to 2024
Therapeutic Apheresis and Dialysis, EarlyView.ABSTRACT Background Uremic toxins are a growing area of research in nephrology, with significant implications in the progression and treatment of chronic kidney disease (CKD) and the management of end‐stage kidney disease (ESKD). This bibliometric analysis aims to evaluate the global research trends, key contributors, and the impact of publications in ...
Yuh‐Shan Ho +7 more
wiley +1 more source
Malay sentiment analysis based on combined classification approaches and Senti-lexicon algorithm.
PLoS ONE, 2018 Sentiment analysis techniques are increasingly exploited to categorize the opinion text to one or more predefined sentiment classes for the creation and automated maintenance of review-aggregation websites.
Ahmed Al-Saffar +5 more
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Future Internet, 2019 Text sentiment analysis is an important but challenging task. Remarkable success has been achieved along with the wide application of deep learning methods, but deep learning methods dealing with text sentiment classification tasks cannot fully exploit ...
Wenkuan Li +3 more
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SSentiA: A Self-supervised Sentiment Analyzer for classification from unlabeled data
Machine Learning with Applications, 2021 In recent years, supervised machine learning (ML) methods have realized remarkable performance gains for sentiment classification utilizing labeled data. However, labeled data are usually expensive to obtain, thus, not always achievable.
Salim Sazzed, Sampath Jayarathna
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