Makale detayı · 2017
A feature selection model based on genetic rank aggregation for text sentiment classification
- Yıl
- 2017
- Tür
- article
Veri kaynağı ayrımı
- YÖKSİS YÖKSİS makale kaydı
- YÖKSİS dergi adı Journal of Information Science
- Katalog eşleşmesi (ISSN) Journal of Information Science
- OpenAlex OpenAlex zenginleştirmesi (özet, atıf, konular)
Özet
OpenAlex · İngilizce
Sentiment analysis is an important research direction of natural language processing, text mining and web mining which aims to extract subjective information in source materials. The main challenge encountered in machine learning method-based sentiment classification is the abundant amount of data available. This amount makes it difficult to train the learning algorithms in a feasible time and degrades the classification accuracy of the built model. Hence, feature selection becomes an essential task in developing robust and efficient classification models whilst reducing the training time. In text mining applications, individual filter-based feature selection methods have been widely utilized owing to their simplicity and relatively high performance. This paper presents an ensemble approach for feature selection, which aggregates the several individual feature lists obtained by the different feature selection methods so that a more robust and efficient feature subset can be obtained. In order to aggregate the individual feature lists, a genetic algorithm has been utilized. Experimental evaluations indicated that the proposed aggregation model is an efficient method and it outperforms individual filter-based feature selection methods on sentiment classification.
Konular
Atıflar
OpenAlex cited_by_count. WoS veya Scopus atıf sayısı değildir; o kaynaklar için ayrı kolon yoktur.
387 atıf
OpenAlex cited_by_count (önbellek / veritabanı)
Yerel katalogda bu makaleye atıf yapan 25 yayın (OpenAlex referans eşleşmesi; tam dünya listesi değildir).
- Ensemble of keyword extraction methods and classifiers in text classification 2016
- Ensemble of keyword extraction methods and classifiers in text classification 2016
- A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification 2016
- A multiobjective weighted voting ensemble classifier based on differential evolution algorithm for text sentiment classification 2016
- A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification 2017
- A hybrid ensemble pruning approach based on consensus clustering and multi-objective evolutionary algorithm for sentiment classification 2017
- Bidirectional convolutional recurrent neural network architecture with group-wise enhancement mechanism for text sentiment classification 2022
- An ensemble scheme based on language function analysis and feature engineering for text genre classification 2018
- Parçacık sürüsü eniyilemesine dayalı yığılmış genelleme yöntemi ve metin sınıflandırma üzerinde uygulanması 2018
- Ensemble of Classifiers and Term Weighting Schemes for Sentiment Analysis in Turkish 2021