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Rule Based Fuzzy Computing Approach on Self-Supervised Sentiment Polarity Classification with Word Sense Disambiguation in Machine Translation for Hindi Language

https://doi.org/10.1145/3574130
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What this work says

Outgoing claims: the papers this work cites, builds on, or argues with.

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Recognizing Emotion Presence in Natural Language Sentences
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Ranking Tourist Attractions through Online Reviews: A Novel Method with Intuitionistic and Hesitant Fuzzy Information Based on Sentiment Analysis
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Aspect-based sentiment analysis of mobile phone reviews using LSTM and fuzzy logic
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Sentiment analysis in Facebook and its application to e-learning
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Document-level sentiment classification: An empirical comparison between SVM and ANN
inferredcites →https://doi.org/10.1016/j.eswa.2016.03.028openalex-snapshot
Classification of sentiment reviews using n-gram machine learning approach
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Social media contents based sentiment analysis and prediction system
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Fuzzy rule based unsupervised sentiment analysis from social media posts
inferredcites →https://doi.org/10.1016/j.fss.2014.01.015openalex-snapshot
Cost-sensitive linguistic fuzzy rule based classification systems under the MapReduce framework for imbalanced big data
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Fuzzy logic—a personal perspective
inferredcites →https://doi.org/10.1016/j.ipm.2019.02.018openalex-snapshot
Deep learning-based sentiment classification of evaluative text based on Multi-feature fusion
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E-commerce product review sentiment classification based on a naïve Bayes continuous learning framework
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Fuzzy logic applied to opinion mining: A review
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WITHDRAWN: Clustering Yelp’s sentiment data through various approaches and estimating the error rate
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An Ensemble Classification System for Twitter Sentiment Analysis
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Sentiment analysis of financial news using unsupervised approach
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An experiment in linguistic synthesis with a fuzzy logic controller
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Using Machine Learning and Thematic Analysis Methods to Evaluate Mental Health Apps Based on User Reviews
inferredcites →https://doi.org/10.1109/fuzz-ieee.2018.8491492openalex-snapshot
An ANEW based Fuzzy Sentiment Analysis Model
inferredcites →https://doi.org/10.1109/icccnt49239.2020.9225646openalex-snapshot
Fuzzy Interpretation of Word Polarity Scores for Unsupervised Sentiment Analysis
inferredcites →https://doi.org/10.1109/icicct.2017.7975226openalex-snapshot
Exploiting expectation maximization algorithm for sentiment analysis of product reviews
inferredcites →https://doi.org/10.1109/icitacee.2017.8257715openalex-snapshot
Sentiment analysis on Twitter posts: An analysis of positive or negative opinion on GoJek
inferredcites →https://doi.org/10.1109/ictai.2014.70openalex-snapshot
Sentiment Analysis: Towards a Tool for Analysing Real-Time Students Feedback
inferredcites →https://doi.org/10.1109/iea.2018.8387151openalex-snapshot
Sentiment analysis of Twitter corpus related to artificial intelligence assistants
inferredcites →https://doi.org/10.1109/mcg.2020.3000359openalex-snapshot
Augmented Reality and Virtual Reality Transforming Spinal Imaging Landscape: A Feasibility Study
inferredcites →https://doi.org/10.1109/mis.2013.34openalex-snapshot
YouTube Movie Reviews: Sentiment Analysis in an Audio-Visual Context
inferredcites →https://doi.org/10.1109/sai.2017.8252275openalex-snapshot
Two simple and effective ensemble classifiers for Twitter sentiment analysis
inferredcites →https://doi.org/10.1109/t-affc.2011.1openalex-snapshot
SentiFul: A Lexicon for Sentiment Analysis
inferredcites →https://doi.org/10.1109/tac.1997.633847openalex-snapshot
Neuro-Fuzzy and Soft Computing-A Computational Approach to Learning and Machine Intelligence [Book Review]
inferredcites →https://doi.org/10.1109/taffc.2019.2926724openalex-snapshot
All-in-One: Emotion, Sentiment and Intensity Prediction Using a Multi-Task Ensemble Framework
inferredcites →https://doi.org/10.1109/tfuzz.2013.2243153openalex-snapshot
IVTURS: A Linguistic Fuzzy Rule-Based Classification System Based On a New Interval-Valued Fuzzy Reasoning Method With Tuning and Rule Selection
inferredcites →https://doi.org/10.1109/tfuzz.2017.2688349openalex-snapshot
A Fast and Accurate Rule-Base Generation Method for Mamdani Fuzzy Systems
inferredcites →https://doi.org/10.1109/tkde.2013.116openalex-snapshot
Interpreting the Public Sentiment Variations on Twitter
inferredcites →https://doi.org/10.1145/3418059openalex-snapshot
Unsupervised Neural Machine Translation for Similar and Distant Language Pairs
inferredcites →https://doi.org/10.1145/3469721openalex-snapshot
Low Resource Neural Machine Translation: Assamese to/from Other Indo-Aryan (Indic) Languages
inferredcites →https://doi.org/10.1145/3524300openalex-snapshot
Low-resource Neural Machine Translation: Methods and Trends
inferredcites →https://doi.org/10.1155/2015/715730openalex-snapshot
Sentiment Analysis Using Common-Sense and Context Information
inferredcites →https://doi.org/10.1186/s13388-015-0024-xopenalex-snapshot
Improved lexicon-based sentiment analysis for social media analytics
inferredcites →https://doi.org/10.1609/aaai.v32i1.11559openalex-snapshot
SenticNet 5: Discovering Conceptual Primitives for Sentiment Analysis by Means of Context Embeddings
inferredcites →https://doi.org/10.1609/icwsm.v8i1.14550openalex-snapshot
VADER: A Parsimonious Rule-Based Model for Sentiment Analysis of Social Media Text
inferredcites →https://doi.org/10.18653/v1/2020.semeval-1.100openalex-snapshot
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inferredcites →https://doi.org/10.18653/v1/d18-1101openalex-snapshot
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inferredcites →https://doi.org/10.18653/v1/d18-1399openalex-snapshot
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inferredcites →https://doi.org/10.18653/v1/s19-2062openalex-snapshot
UAIC at SemEval-2019 Task 3: Extracting Much from Little
inferredcites →https://doi.org/10.2200/s00416ed1v01y201204hlt016openalex-snapshot
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inferredcites →https://doi.org/10.3115/1621474.1621487openalex-snapshot
SemEval-2007 task 14
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