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Performance Evaluation and Comparison using Deep Learning Techniques in Sentiment Analysis
2021
Journal of Soft Computing Paradigm
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One of the most common applications of deep learning algorithms is sentiment analysis. ...
The first step is the development of sentiment classifiers with deep learning, which can be used as the baseline for comparing the performance. ...
The proposed work addresses the basic framework required to characterize the already available sentiment analysis based on the traditional research methodologies with respect to deep learning techniques ...
doi:10.36548/jscp.2021.2.006
fatcat:onnac737d5flpdqbyapylolu4a
A Precisely Xtreme-Multi Channel Hybrid Approach For Roman Urdu Sentiment Analysis
2020
IEEE Access
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[62] have utilized a deep learning based approach for the task of Roman Urdu sentiment analysis. ...
A very limited sentiment analysis work exists for Roman Urdu which can be classified into lexicon based [18] , machine learning, and deep learning based approaches [19] , [20] , [21] , [22] . ...
For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/ developed experimental dataset will be publicly available. ...
doi:10.1109/access.2020.3030885
fatcat:74xtllokurhfjdzpjg2ispgaxq
A Review of Hybrid and Ensemble in Deep Learning for Natural Language Processing
[article]
2023
arXiv
pre-print
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language-driven applications through ensemble deep learning in NLP. ...
such as Sentiment Analysis, Named Entity Recognition, Machine Translation, Question Answering, Text Classification, Generation, Speech Recognition, Summarization, and Language Modeling. ...
Base Models for NLP This section delves into the base models employed in Natural Language Processing (NLP), with a specific focus on sentiment analysis. ...
arXiv:2312.05589v1
fatcat:wjqejbp5fbhsjbkukwq4jngdsy
Advanced Analytics with AI in Data Engineering
2024
Zenodo
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Emphasis is placed on machine learning, deep learning, and natural language processing as key components of AI-driven analytics. ...
Addressing issues related to data privacy, security, interpretability, and bias, the paper explores potential avenues for advancement, including the integration of emerging technologies for enhanced efficiency ...
Document Classification Categorizing documents based on content is streamlined through NLP. ...
doi:10.5281/zenodo.10686010
fatcat:2fyv6umjvzhkpik4edebfczztu
Deep Learning Based Techniques for Sentiment Analysis: A Survey
2021
Informatica (Ljubljana, Tiskana izd.)
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Sentiment analysis methods focused on deep learning over the past five years are analyzed in this review. ...
Sentiment classification, which attempts to automatically classify opinionated text as positive, negative, or neutral, is a fundamental activity of sentiment analysis. ...
This section describes the efforts to integrate deep learning models for sentiment analysis by various researchers. ...
doi:10.31449/inf.v45i7.3674
fatcat:a724vfd2p5bbrbnrxpojynstx4
Advancements in Deep Learning for Natural Language Processing in Software Applications
2020
Zenodo
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This paper provides a comprehensive review of the latest developments in leveraging deep learning for NLP tasks and its integration into software applications. ...
This paper provides an overview of the recent progress and innovations in leveraging deep learning models for NLP tasks and their integration into software applications. ...
Task 1: Sentiment Analysis For the task of sentiment analysis, we evaluated the performance of our deep learning models on the IMDb movie review dataset. ...
doi:10.5281/zenodo.10779226
fatcat:p6z3vtngcrfyxgjyinx7wdphtm
Enhanced sentiment analysis based on improved word embeddings and XGboost
2023
International Journal of Power Electronics and Drive Systems (IJPEDS)
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This article proposes a novel method, improved words vector for sentiments analysis (IWVS), using XGboost to improve the F1-score of sentiment classification. ...
We compared the F1-score of sentiment classification using our method via different machine learning models and sentiment datasets. ...
There are two types of sentiment categorization techniques: Polarized lexicon-based methods and machine learning methods like deep learning [17] . ...
doi:10.11591/ijece.v13i2.pp1827-1836
fatcat:4fnbcguiyfgvvav7qmcfvo6eve
Visualizing Health: Advancing Natural Language Processing Through Data Visualization in Healthcare
2023
International Journal of Data Science and Big Data Analytics
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The study encompasses a comprehensive analysis of health data derived from medical documentation, social media, and biological literature. ...
This paper explores the transformative integration of Natural Language Processing (NLP) with data visualization in the realm of healthcare informatics. ...
Catalyst for Future Research and Innovation Perhaps most significantly, the integration of NLP with data visualization serves as a catalyst for future research and innovation. ...
doi:10.51483/ijdsbda.3.2.2023.1-18
fatcat:obd2q7vicjetdcxq6u2c45f4we
A Review of Sentiment Analysis Techniques
2020
International Journal of Computer Applications
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This review paper describes the latest studies which concern with fulfillment deep learning models to sentiment analysis as deep neural networks, convolutional neural networks, and others to solve various ...
The challenge which faces sentiment analysis is the lack of labeled data in NLP. ...
A deep CNN model for visual sentiment analysis using Caffe and Python was implemented on Linux X86-64, and the the Sentiment Analysis Machine Learning Lexicon Based Approach Approach Supervised Learning ...
doi:10.5120/ijca2020920480
fatcat:gmnsigfg2batxkpo3xoswwrjbq
Sentiment analysis of Indonesian hotel reviews: from classical machine learning to deep learning
2021
IJAIN (International Journal of Advances in Intelligent Informatics)
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With the advances in deep learning paradigms, many algorithms have been developed that can be used in sentiment analysis tasks. ...
Deep learning has excellent capabilities for recognizing this type of data. ...
Acknowledgment The authors thank the Directorate of Research and Development, under the Ministry of Research and Technology/National Agency for Research and Innovation, Indonesia, for supporting this research ...
doi:10.26555/ijain.v7i3.737
fatcat:vpdkv5fcdjctja5hpzx3jtgpta
Detailed Technical Programme Schedule
2020
2020 Sixth International Conference on Parallel, Distributed and Grid Computing (PDGC)
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and Deep Learning based Methods for Digital Image Ashwani Kumar, Vardhaman Engineering College, Hyderabad, Telangana , Jawaharlal Nehru University, New Delhi Neural Networks and Deep Learning based Methods ...
University of Information Technology, Waknaghat Paper Title Machine Learning Technique for Wireless Sensor Networks Novel Machine Learning Approach for Sentiment Analysis of Real Time Twitter Data with ...
doi:10.1109/pdgc50313.2020.9315322
fatcat:4ndwytytovb7xkntz7bmaurj6a
SENTIMENT ANALYSIS FOR SOCIAL MEDIA: A SURVEY
2021
Journal of Computer Science and Cybernetics
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This survey presents a summary of the necessary stages for building a complete model to be used in sentiment analysis. ...
Sentiments from opinions are a valuable data source for solving many issues. Therefore, sentiment analysis has developed into one of the most popular natural language processing fields. ...
This lexicon is created based on sentic computing [12] , a novel multidisciplinary paradigm for sentiment analysis. ...
doi:10.15625/1813-9663/37/4/15892
fatcat:2dgv3sygovgelk3mffmvnmokay
Extractive Summarization for Explainable Sentiment Analysis using Transformers
2021
Extended Semantic Web Conference
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Here we propose two different methodologies to exploit the performance of these models in a task of sentiment analysis and, in the meantime, to generate a summary that serves as an explanation of the decision ...
In recent years, the paradigm of eXplainable Artificial Intelligence (XAI) systems has gained wide research interest and beyond. ...
We could also define our models as deep learning-based (because, of course, Transformers are deep neural networks models) and informative (because the extracted summaries contain important information ...
dblp:conf/esws/BaccoCDM21
fatcat:6cjowepprfh2vck3m7675fw2s4
Comparative Sentiment Analysis of App Reviews
[article]
2020
arXiv
pre-print
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Sentiment analysis, by machine learning algorithms employing NLP, is used to explicitly uncover and interpret the emotions. ...
We applied machine learning algorithms using the TF-IDF text representation scheme and the performance was evaluated on the ensemble learning method. ...
[15] have collected instructors reviews from students for opinion mining using deep learning paradigm. ...
arXiv:2006.09739v1
fatcat:s3ubvxtxmrdkpfls4eibr4viye
Sentiment Analysis for Sinhala Language using Deep Learning Techniques
[article]
2020
arXiv
pre-print
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For sentiment analysis, there exists only two previous research with deep learning approaches, which focused only on document-level sentiment analysis for the binary case. ...
Due to the high impact of the fast-evolving fields of machine learning and deep learning, Natural Language Processing (NLP) tasks have further obtained comprehensive performances for highly resourced languages ...
[2016] conducted the first experiment on deep learning based sentiment analysis for Hindi language. ...
arXiv:2011.07280v1
fatcat:47uivasos5gb5cplnw7fe2khx4
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