Feature selection plays an important role in text classification. In the process of text classification, each word is considered as a feature which creates a huge number of features. However, one of the most main issue in text classification is high dimensioanl feature space. excessive number of feature increase the computational cost, but also may degrades the accuracy. Therefore, feature selection selects a set of best features for the target. There are mainly four categories for feature selection methods: filter, wrapper, hybrid and embedded.
Here are the list of paper when I was doing research on feature selection.
| Author | Title | Year | Publishing | Journal Ranking |
|---|---|---|---|---|
| Uysal, A.K. | An improved global feature selection scheme for text classification | 2015 | Expert Systems With Applications | Q1 |
| Adel, A., Omar, N., Al-Shabi, A. | A Comparative Study of Combined Feature Selection Methods for Arabic Text Classification | 2014 | Journal of Computer Science | --- |
| Harish, B. S., Revanasiddapa, M. B. | A Comprehensive Survey on various Feature Selection Methods to Categorize Text Documents | 2017 | International Journal of Computer Applications | --- |
| Labani, M., Moradi, P., Ahmadizar, F., Jalili, M. | A Novel Multivariate Filter Method for Feature Selection in Text Classification Problems | 2018 | Engineering Applications of Artificial Intelligence | --- |
| Uysal, A.K., Gunal, S. | A Novel Probabilistic Feature Selection Method For Text Classification | 20212 | Knowledge-Based Systems | --- |
| Guru, D.S., Suhil, M., Raju, L.N., Kumar, N.V. | An Alternative Framework for Univariate Filter based Feature Selection for Text Categorization | 2018 | Pattern Recognition Letters | --- |
| Ogura, H., Amano, H., Kondo, M. | Comparison of metrics for feature selection in imbalanced text classification | 2011 | Expert Systems with Applications | Q1 |
| Paradis, F., Nie, J. | Contextual feature selection for text classification | 2007 | Information Processing and Management | --- |
| Raho, G., Al-Shalabi, R., Kanaan, G., Nassar, A. | Different Classification Algorithms Based on Arabic Text Classification_ Feature Selection Comparative Study | 2015 | International Journal of Advanced Computer Science and Applications | --- |
| Yin, X., Liu, C., Han, Z. | Feature combination using boosting | 2005 | Pattern Recognition Letters | --- |
| Gao, W., Hu, L., Zhang, P., Wang, F. | Feature selection by integrating two groups of feature evaluation criteria | 2018 | Expert Systems with Applications | Q1 |
| Chouaib, H., Terrades, O. R., Tabbone, S., Cloppet, F., Vincet, N. | Feature Selection Combining Genetic Algorithm and Adaboost Classifier | 2008 | 19th International Conference on Pattern Recognition | --- |
| El Barbary O.G., Salama, A.S. | Feature selection for document classification based on topology | 2018 | Egyptian Informatics Journal | --- |
| Chen J., Huang, H., Tian, S., Qu, Y. | Feature selection for text classification with Naive Bayes | 2009 | Expert Systems with Applications | Q1 |
| Bahassine, S., Madani, A., Al-Sarem, M., Kissi, M. | Feature selection using an improved Chi-square for Arabic text classification | 2018 | Journal of King Saud University - Computer and Information Sciences | --- |
| Shang, C., Li, M., Feng, S., Jiang, Q., Fan, J. | Feature selection via maximizing global information gain for text classification | 2013 | Knowledge-Based Systems | --- |
| Feng, G., Guo, J., Jing, B., Sun, T. | Feature Subset Selection Using Naive Bayes for Text Classification | 2015 | Pattern Recognition Letters | --- |
| Che, J., Yang, Y., Li, L., Bai, X., Zhang, S., Deng, C. | Maximum relevance minimum common redundancy feature selection for nonlinear data | 2017 | Information Sciences | --- |
| Rehman, A., Javed, K., Babri, H.A., Saeed, M. | Relative discrimination criterion - A novel feature ranking method for text data | 2015 | Expert Systems with Applications | --- |
| Author | Title | Year | Publishing | Journal Ranking |
|---|---|---|---|---|
| Wang, Y., Feng, L., | Hybrid Feature Selection using Component Co-occurrence based Feature Relevant Measurement | 2018 | Expert Systems with Applications | Q1 |
| Alghamdi, H., Selamat, A., | The Hybrid Feature Selection k-means Method for Arabic Webpage Classification | 2014 | Jurnal Teknologi | --- |
| Author | Title | Year | Publishing | Journal Ranking |
|---|---|---|---|---|
| Belkebir, R., Guessoum, A. | A Hybrid BSO-Chi2-SVM Approach to Arabic Text Categorization | 2013 | ACS International Conference on Computer Systems and Applications (AICCSA) | --- |
| Costa, H., Galvao, L. R., Merschmann, L. H. C., Souza, M. J. F. | A VNS algorithm for feature selection in hierarchical classification context | 2018 | Electronic Notes in Discrete Mathematics | --- |
| Subanya, B., Rajalaxmi, R. R. | Feature Selection using Artificial Bee Colony for Cardiovascular Disease Classification | 2014 | International Conference on Electronics and Communication System | --- |
| Indriyani, Gunawan, W., Rakhmadi, A. | Filter-Wrapper Approach to Feature Selection Using PSO-GA for Arabic Document Classification with Naive Bayes Multinomial | 2015 | Journal of Computer Engineering | --- |
| Banati, H., Bajaj, M. | Fire Fly Based Feature Selection Approach | 2011 | International Journal of Computer Science Issues | --- |
| Marie-Sainte, S. L., Alalyani, N. | Firefly Algorithm based Feature Selection for Arabic Text Classification | 2018 | Journal of King Saud University - Computer and Information Sciences | --- |
| Alghamadi, H. S., Tang, H. L. | Hybrid ACO and TOFA Feature Selection Approach for Text Classification | 2012 | IEEE Congress on Evolutionary Computation | --- |
| Mesleh, A. M., Kanaan, G. | Support Vector Machine Text Classification System_ Using Ant Colony Optimization Based Feature Subset Selection | 2008 | International Conference on Computer Engineering & Systems | --- |
| Aghdam, M. H., Aghaee, N. G., Basiri, M. E. | Text feature selection using ant colony optimization | 2009 | Expert Systems with Applications | Q1 |
| Zahran, B. M., Kanaan, G. | Text Feature Selection using Particle Swarm Optimization Algorithm | 2009 | World Applied Sciences Journal | --- |
| Emary, E., Zawbaa, H. M., Ghany, K. K. A., Hassanien A. E., PARV, B. | Firefly Optimization Algorithm for Feature Selection | 2015 | Balkan Conference in Informatics | --- |
| Lu, Y., Liang, M., Ye, Z., Cao, L. | Improved particle swarm optimization in algorithm and its application in text feature selection | 2015 | Applied Soft Computing | --- |
| Kushwaha, N., Pant, M. | Link based BPSO for feature selection in big data text clustering | 2018 | Future Generation Computer Systems | --- |
| Lim, H., Lee, J., Kim, D. W. | Optimization approach for feature selection in multi-label classification | 2017 | Pattern Recognition Letters | --- |
| Xue, B., Zhang, M., Browne, W. N. | Particle Swarm Optimization for Feature Selection in Classification_ A Multi-Objective Approach | 2012 | IEEE Transactions on Cybernetics | --- |
| Ahmad, S. R., Yusop, N. M. M., Bakar, A. A., Yaakub, M. R. | Statistical Analysis for Validating ACO-KNN Algorithm as Feature Selection in Sentiment Analysis | 2017 | International Conference on Applied Science and Technology | --- |
| Sarac, E., Ozel, S. A. | Web Page Classification Using Firefly Optimization | 2013 | IEEE INISTA | --- |
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