Results 31 to 40 of about 17,106 (265)

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
doaj   +1 more source

A survey of text aspect-based sentiment classification

Journal of Hebei University of Science and Technology, 2020
With the development of deep learning, aspect-based sentiment classification has achieved a lot of results in a single field and a single language, but there is room for improvement in multi-fields.
Shengwang LI, Yi YANG, Yunfeng XU, Yan ZHANG   +3 more
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Advancement in Bangla Sentiment Analysis: A Comparative Study of Transformer-Based and Transfer Learning Models for E-commerce Sentiment Classification

Journal of Information Systems Engineering and Business Intelligence, 2023
Background: As a direct result of the Internet's expansion, the quantity of information shared by Internet users across its numerous platforms has increased.
Zishan Ahmed, Shakib Sadat Shanto, Akinul Islam Jony   +2 more
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Lifelong Learning for Sentiment Classification [PDF]

Proceedings of the 53rd Annual Meeting of the Association for Computational Linguistics and the 7th International Joint Conference on Natural Language Processing (Volume 2: Short Papers), 2015
This paper proposes a novel lifelong learning (LL) approach to sentiment classification. LL mimics the human continuous learning process, i.e., retaining the knowledge learned from past tasks and use it to help future learning. In this paper, we first discuss LL in general and then LL for sentiment classification in particular. The proposed LL approach
Zhiyuan Chen 0001, Nianzu Ma, Bing Liu 0001   +2 more
openaire   +2 more sources

A comparative performance evaluation of neural network based approach for sentiment classification of online reviews

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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Adversarial Attack on Sentiment Classification [PDF]

Proceedings of the 2019 ACL Workshop BlackboxNLP: Analyzing and Interpreting Neural Networks for NLP, 2019
In this paper, we propose a white-box attack algorithm called “Global Search” method and compare it with a simple misspelling noise and a more sophisticated and common white-box attack approach called “Greedy Search”. The attack methods are evaluated on the Convolutional Neural Network (CNN) sentiment classifier trained on the IMDB movie review dataset.
Yi-Ting (Alicia) Tsai, Min-Chu Yang, Han-Yu Chen   +2 more
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On the Feature Selection and Classification Based on Information Gain for Document Sentiment Analysis

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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Improving the accuracy of sentiment analysis using a linguistic rule-based feature selection method in tourism reviews

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, T. Sasi Rooba, S. Chakaravarthi   +2 more
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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
openaire   +2 more sources

Comparative Study of Deep Learning-Based Sentiment Classification

IEEE Access, 2020
The purpose of sentiment classification is to determine whether a particular document has a positive or negative nuance. Sentiment classification is extensively used in many business domains to improve products or services by understanding the opinions ...
Seungwan Seo, Czangyeob Kim, Haedong Kim, Kyounghyun Mo, Pilsung Kang   +4 more
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