Results 21 to 30 of about 265,995 (181)
Multi-domain sentiment classification [PDF]
Proceedings of the 46th Annual Meeting of the Association for Computational Linguistics on Human Language Technologies Short Papers - HLT '08, 2008 This paper addresses a new task in sentiment classification, called multi-domain sentiment classification, that aims to improve performance through fusing training data from multiple domains. To achieve this, we propose two approaches of fusion, feature-level and classifier-level, to use training data from multiple domains simultaneously.
Shoushan Li, Chengqing Zong
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Sentiment Classification Method Based on BLSTM and Aspect Attention Module [PDF]
Jisuanji gongcheng, 2020 Aspect-Based Sentiment Analysis(ABSA) has been widely used in text information mining,but can hardly extract accurate feature information when the sentiment polarity of a sentence is fuzzy or a sentence has sentiment polarities of multiple aspects,which ...
PENG Zhuliang, LIU Bowen, FAN Cheng'an, WANG Jie, XIAO Ming, LIAO Zeen
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Bilingual Sentiment Embeddings: Joint Projection of Sentiment Across Languages [PDF]
, 2018 Sentiment analysis in low-resource languages suffers from a lack of annotated corpora to estimate high-performing models. Machine translation and bilingual word embeddings provide some relief through cross-lingual sentiment approaches.
Barnes, Jeremy +2 more
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Journal of King Saud University: Computer and Information Sciences, 2016 The aim of sentiment classification is to efficiently identify the emotions expressed in the form of text messages. Machine learning methods for sentiment classification have been extensively studied, due to their predominant classification performance ...
G. Vinodhini, R.M. Chandrasekaran
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Interactive Attention Networks for Aspect-Level Sentiment Classification [PDF]
, 2017 Aspect-level sentiment classification aims at identifying the sentiment polarity of specific target in its context. Previous approaches have realized the importance of targets in sentiment classification and developed various methods with the goal of ...
Li, Sujian +3 more
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Measurement: Sensors, 2023 Sentiment Analysis technique involves extracting the relevant information from Unstructured User Reviews (UUR) dataset fetched from online and classifying them into appropriate positive and negative comments for making decisions.
N. Saraswathi +2 more
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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
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Linguistically Regularized LSTM for Sentiment Classification [PDF]
Proceedings of the 55th Annual Meeting of the Association for
Computational Linguistics (Volume 1: Long Papers), 2017 Sentiment understanding has been a long-term goal of AI in the past decades. This paper deals with sentence-level sentiment classification. Though a variety of neural network models have been proposed very recently, however, previous models either depend on expensive phrase-level annotation, whose performance drops substantially when trained with only ...
Qian, Qiao +3 more
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Applied Computational Intelligence and Soft Computing, 2018 Sentiment analysis in a movie review is the needs of today lifestyle. Unfortunately, enormous features make the sentiment of analysis slow and less sensitive. Finding the optimum feature selection and classification is still a challenge.
Asriyanti Indah Pratiwi, Adiwijaya
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Better Document-level Sentiment Analysis from RST Discourse Parsing [PDF]
, 2015 Discourse structure is the hidden link between surface features and document-level properties, such as sentiment polarity. We show that the discourse analyses produced by Rhetorical Structure Theory (RST) parsers can improve document-level sentiment ...
Bhatia, Parminder +2 more
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