-
1
-
-
84876036807
-
Using micro-documents for feature selection: The case of ordinal text classification
-
Baccianella, S., Esuli, A., & Sebastiani, F. (2013). Using micro-documents for feature selection: The case of ordinal text classification. Expert Systems with Applications, 40, 4687-4696.
-
(2013)
Expert Systems with Applications
, vol.40
, pp. 4687-4696
-
-
Baccianella, S.1
Esuli, A.2
Sebastiani, F.3
-
2
-
-
77951430107
-
Distributional word clusters vs. words for text categorization
-
Bekkerman, R., El-Yaniv, R., Tishby, N., & Winter, Y. (2003). Distributional word clusters vs. words for text categorization. Journal of Machine Learning Research, 3, 1183-1208.
-
(2003)
Journal of Machine Learning Research
, vol.3
, pp. 1183-1208
-
-
Bekkerman, R.1
El-Yaniv, R.2
Tishby, N.3
Winter, Y.4
-
3
-
-
84888289865
-
Speeding up incremental wrapper feature subset selection with Naive Bayes classifier
-
Bermejo, P., Gámez, J., & Puerta, J. (2014). Speeding up incremental wrapper feature subset selection with Naive Bayes classifier. Knowledge-Based Systems, 55, 140-147.
-
(2014)
Knowledge-Based Systems
, vol.55
, pp. 140-147
-
-
Bermejo, P.1
Gámez, J.2
Puerta, J.3
-
4
-
-
0003802343
-
-
Wadsworth International Group
-
Breiman, L., Friedman, J., Stone, C., & Olshen, R. (1984). Classification and regression trees. Wadsworth International Group
-
(1984)
Classification and Regression Trees
-
-
Breiman, L.1
Friedman, J.2
Stone, C.3
Olshen, R.4
-
5
-
-
70349247055
-
Modeling hidden topics on document manifold
-
Cai, D., Mei, Q., Han, J., & Zhai, C. (2008). Modeling hidden topics on document manifold. In Proceeding of the 17th ACM conference on information and knowledge management (CIKM'08) (pp. 911-920).
-
(2008)
Proceeding of the 17th ACM Conference on Information and Knowledge Management (CIKM'08)
, pp. 911-920
-
-
Cai, D.1
Mei, Q.2
Han, J.3
Zhai, C.4
-
6
-
-
37349077709
-
Multilabel text categorization based on a new linear classifier learning method and a category-sensitive refinement method
-
Chang, Y., Chen, S., & Liau, C. (2008). Multilabel text categorization based on a new linear classifier learning method and a category-sensitive refinement method. Expert Systems with Applications, 34, 1948-1953.
-
(2008)
Expert Systems with Applications
, vol.34
, pp. 1948-1953
-
-
Chang, Y.1
Chen, S.2
Liau, C.3
-
7
-
-
58349094507
-
Feature selection for text classification with Naive Bayes
-
Chen, J., Huang, H., Tian, S., & Qu, Y. (2009). Feature selection for text classification with Naive Bayes. Expert Systems with Applications, 36, 5432-5435.
-
(2009)
Expert Systems with Applications
, vol.36
, pp. 5432-5435
-
-
Chen, J.1
Huang, H.2
Tian, S.3
Qu, Y.4
-
9
-
-
2942731012
-
An extensive empirical study of feature selection metrics for text classification
-
Forman, G. (2003). An extensive empirical study of feature selection metrics for text classification. The Journal of Machine Learning Research, 3, 1289-1305.
-
(2003)
The Journal of Machine Learning Research
, vol.3
, pp. 1289-1305
-
-
Forman, G.1
-
10
-
-
19744376557
-
Best terms: An efficient feature-selection algorithm for text categorization
-
Fragoudis, D., Meretakis, D., & Likothanassis, S. (2005). Best terms: An efficient feature-selection algorithm for text categorization. Knowledge and Information Systems, 8, 16-33.
-
(2005)
Knowledge and Information Systems
, vol.8
, pp. 16-33
-
-
Fragoudis, D.1
Meretakis, D.2
Likothanassis, S.3
-
16
-
-
31144448615
-
Using simulated annealing to optimize the feature selection problem in marketing applications
-
Meiri, R., & Zahavi, J. (2006). Using simulated annealing to optimize the feature selection problem in marketing applications. European Journal of Operational Research, 171, 842-858.
-
(2006)
European Journal of Operational Research
, vol.171
, pp. 842-858
-
-
Meiri, R.1
Zahavi, J.2
-
19
-
-
0031630992
-
Learning to classify text from labeled and unlabeled documents
-
Nigam, K., McCallum, A., Thrun, S., & Mitchell, T. (1998). Learning to classify text from labeled and unlabeled documents. In Proceedings of the national conference on artificial intelligence (pp. 792-799).
-
(1998)
Proceedings of the National Conference on Artificial Intelligence
, pp. 792-799
-
-
Nigam, K.1
McCallum, A.2
Thrun, S.3
Mitchell, T.4
-
20
-
-
84865003955
-
A global-ranking local feature selection method for text categorization
-
Pinheiro, R., Cavalcanti, G., Correa, R., & Ren, T. (2012). A global-ranking local feature selection method for text categorization. Expert Systems with Applications, 39, 12851-12857.
-
(2012)
Expert Systems with Applications
, vol.39
, pp. 12851-12857
-
-
Pinheiro, R.1
Cavalcanti, G.2
Correa, R.3
Ren, T.4
-
21
-
-
33744584654
-
Induction of decision trees
-
Quinlan, J. (1986). Induction of decision trees. Machine Learning, 1, 81-106.
-
(1986)
Machine Learning
, vol.1
, pp. 81-106
-
-
Quinlan, J.1
-
23
-
-
0002442796
-
Machine learning in automated text categorization
-
Sebastiani, F. (2002). Machine learning in automated text categorization. ACM Computing Surveys, 34, 1-47.
-
(2002)
ACM Computing Surveys
, vol.34
, pp. 1-47
-
-
Sebastiani, F.1
-
24
-
-
33845622338
-
A novel feature selection algorithm for text categorization
-
Shang, W., Huang, H., Zhu, H., Lin, Y., Qu, Y., & Wang, Z. (2007). A novel feature selection algorithm for text categorization. Expert Systems with Applications, 33, 1-5.
-
(2007)
Expert Systems with Applications
, vol.33
, pp. 1-5
-
-
Shang, W.1
Huang, H.2
Zhu, H.3
Lin, Y.4
Qu, Y.5
Wang, Z.6
-
25
-
-
84885055365
-
Comparison of text feature selection policies and using an adaptive framework
-
Taşci, Ş., & Güngör, T. (2013). Comparison of text feature selection policies and using an adaptive framework. Expert Systems with Applications, 40, 4871-4886.
-
(2013)
Expert Systems with Applications
, vol.40
, pp. 4871-4886
-
-
Taşci, Ş.1
Güngör, T.2
-
26
-
-
84867846144
-
A novel probabilistic feature selection method for text classification
-
Uysal, A., & Gunal, S. (2012). A novel probabilistic feature selection method for text classification. Knowledge-Based Systems, 36, 226-235.
-
(2012)
Knowledge-Based Systems
, vol.36
, pp. 226-235
-
-
Uysal, A.1
Gunal, S.2
-
29
-
-
79957440082
-
A new feature selection algorithm based on binomial hypothesis testing for spam filtering
-
Yang, J., Liu, Y., Liu, Z., Zhu, X., & Zhang, X. (2011). A new feature selection algorithm based on binomial hypothesis testing for spam filtering. Knowledge-Based Systems, 24, 904-914.
-
(2011)
Knowledge-Based Systems
, vol.24
, pp. 904-914
-
-
Yang, J.1
Liu, Y.2
Liu, Z.3
Zhu, X.4
Zhang, X.5
-
30
-
-
84862784257
-
A new feature selection based on comprehensive measurement both in inter-category and intra-category for text categorization
-
Yang, J., Liu, Y., Zhu, X., Liu, Z., & Zhang, X. (2012). A new feature selection based on comprehensive measurement both in inter-category and intra-category for text categorization. Information Processing and Management: An International Journal, 48, 741-754.
-
(2012)
Information Processing and Management: An International Journal
, vol.48
, pp. 741-754
-
-
Yang, J.1
Liu, Y.2
Zhu, X.3
Liu, Z.4
Zhang, X.5
-
31
-
-
34250709795
-
OCFS: Optimal orthogonal centroid feature selection for text categorization
-
ACM
-
Yan, J., Liu, N., Zhang, B., Yan, S., Chen, Z., Cheng, Q., et al. (2005). OCFS: Optimal orthogonal centroid feature selection for text categorization. In Proceedings of the ACM SIGIR conference on research and development in information retrieval (pp. 122-129). ACM.
-
(2005)
Proceedings of the ACM SIGIR Conference on Research and Development in Information Retrieval
, pp. 122-129
-
-
Yan, J.1
Liu, N.2
Zhang, B.3
Yan, S.4
Chen, Z.5
Cheng, Q.6
-
32
-
-
1942451938
-
Feature selection for high-dimensional data: A fast correlation-based filter solution
-
Yu, L., & Liu, H. (2003). Feature selection for high-dimensional data: A fast correlation-based filter solution. In Proceedings of the international conference on machine leaning (pp. 856-863).
-
(2003)
Proceedings of the International Conference on Machine Leaning
, pp. 856-863
-
-
Yu, L.1
Liu, H.2
|