Data-based prediction of sentiments using heterogeneous model ensembles

In this paper, we present an ensemble modeling approach for sentiment analysis using machine learning algorithms. The main goal of sentiment analysis is to develop estimators that are able to identify the sentiment orientation (positive, negative, or neutral) of sentences found in any arbitrary sour...

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Vydáno v:	Soft computing (Berlin, Germany) Ročník 19; číslo 12; s. 3401 - 3412
Hlavní autoři:	Winkler, Stephan, Schaller, Susanne, Dorfer, Viktoria, Affenzeller, Michael, Petz, Gerald, Karpowicz, Michał
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Berlin/Heidelberg Springer Berlin Heidelberg 01.12.2015 Springer Nature B.V
Témata:	Algorithms Artificial Intelligence Artificial neural networks Classification Classifiers Computational Intelligence Consumers Control Data mining Decision trees Dictionaries Empirical analysis Engineering Focus Gaussian process Genetic algorithms German language Keywords Machine learning Mathematical Logic and Foundations Mechatronics Optimization techniques Product reviews Robotics Semantics Sentences Sentiment analysis Social networks Support vector machines Sentiment analysis Heterogeneous model ensembles Machine learning Evolutionary computation
ISSN:	1432-7643, 1433-7479
On-line přístup:	Získat plný text
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