A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification

Sentiment analysis is a critical task of extracting subjective information from online text documents. Ensemble learning can be employed to obtain more robust classification schemes. However, most approaches in the field incorporated feature engineering to build efficient sentiment classifiers. The...

Celý popis

Uloženo v:

Podrobná bibliografie
Vydáno v:	Information processing & management Ročník 53; číslo 4; s. 814 - 833
Hlavní autoři:	Onan, Aytuğ, Korukoğlu, Serdar, Bulut, Hasan
Médium:	Journal Article
Jazyk:	angličtina
Vydáno:	Oxford Elsevier Ltd 01.07.2017 Elsevier Science Ltd
Témata:	Algorithms Candidates Classification Classification schemes Classifiers Clustering Consensus clustering Data mining Elitism Ensemble pruning Evolutionary algorithms Genetic algorithms Libraries Machine learning Multi-objective evolutionary algorithm Multiple objective analysis Objectives Pareto optimum Pruning Ranking Sentiment analysis Sentiment classification Subjectivity Ensemble pruning Multi-objective evolutionary algorithm Consensus clustering Sentiment classification
ISSN:	0306-4573, 1873-5371
On-line přístup:	Získat plný text
Tagy:	Přidat tag Žádné tagy, Buďte první, kdo vytvoří štítek k tomuto záznamu!

Buďte první, kdo okomentuje tento záznam!