International Journal of Advanced Computer Science and Applications · 2020 · 14 citations · 19 references
ComputingComputer ScienceData ScienceComputational LinguisticsMachine LearningNatural Language ProcessingAffective ComputingEmotion RecognitionInformation ExtractionOpinion MiningSentiment AnalysisText MiningConsumer Opinion MiningCustomer InsightsEmotion DetectionOpinion ExtractionPolarity DetectionSentiment ClassificationSentiment FeaturesTextual Sentiment Analysis
Opinion mining (known as sentiment analysis or emotion Artificial Intelligence) holds important roles for e-commerce and benefits to numerous business and organizations. It studies the use of natural language processing, text analysis, computational linguistics, and biometrics to provide us business valuable insights into how people feel about our product brand or service. In this study, we investigate reviews from Amazon Fine Food Reviews dataset including about 500,000 reviews and propose a method to transform reviews into features including Opinion Words which then can be used for reviews classification tasks by machine learning algorithms. From the obtained results, we evaluate useful Opinion Words which can be informative to identify whether the review is positive or negative.
19
Leo Breiman · Machine Learning · 2001 · 126.2K citations · Full text
Greedy function approximation: A gradient boosting machine.
Jerome H. Friedman · The Annals of Statistics · 2001 · 29K citations · Full text
Distributed Representations of Words and Phrases and their Compositionality
Tomáš Mikolov, Ilya Sutskever, Kai Chen et al. · arXiv (Cornell University) · 2013 · 18.1K citations · Full text
J. R. Quinlan · Machine Learning · 1986 · 12.4K citations · Full text
LightGBM: A Highly Efficient Gradient Boosting Decision Tree
Guolin Ke, Qi Meng, Thomas Finley et al. · HAL (Le Centre pour la Communication Scientifique Directe) · 2017 · 9.5K citations · Full text