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Original Articles

Rough set-aided keyword reduction for text categorization

Pages 843-873 | Published online: 30 Nov 2010

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Subhasis Das & Anindya Ghosh. (2022) Decision Rule Prediction for Assessment of Rotor Spun Cotton Yarn Strength Using Rough Set. Journal of Natural Fibers 19:17, pages 15919-15929.
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Niharendu Bikash Kar, Anindya Ghosh, Subhasis Das & Debamalya Banerjee. (2022) Estimation of raw silk quality using rough set theory. The Journal of The Textile Institute 113:11, pages 2352-2357.
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Aayush Singha Roy & Niladri Chatterjee. (2022) Forecasting of Indian Stock Market Using Rough Set and Fuzzy-Rough Set Based Models. IETE Technical Review 39:5, pages 1105-1113.
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Peng Yang & Qintian Yang. (2014) Empirical Mode Decomposition and Rough Set Attribute Reduction for Ultrasonic Flaw Signal Classification. International Journal of Computational Intelligence Systems 7:3, pages 481-492.
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Walid Moudani, Ahmad Shahin, Fadi Shakik & Félix Mora-Camino. (2011) Dynamic programming applied to rough sets attribute reduction. Journal of Information and Optimization Sciences 32:6, pages 1371-1397.
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Salsabil Trabelsi & Zied Elouedi. (2010) Heuristic method for attribute selection from partially uncertain data using rough sets. International Journal of General Systems 39:3, pages 271-290.
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P. S. V. S. Sai Prasad, H. Bala Subrahmanyam & Praveen Kumar Singh. 2017. Distributed Computing and Internet Technology. Distributed Computing and Internet Technology 58 69 .
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Amit Paul, Jaya Sil & Chitrangada Das Mukhopadhyay. 2015. Computational Intelligence in Data Mining - Volume 1. Computational Intelligence in Data Mining - Volume 1 459 467 .
M. Bagyamathi & H. Hannah Inbarani. 2015. Big Data in Complex Systems. Big Data in Complex Systems 173 204 .
Yasuo Kudo & Tetsuya Murai. (2014) Some properties of interrelated attributes in relative reducts for interrelationship mining. Some properties of interrelated attributes in relative reducts for interrelationship mining.
Adriana da Silva Jacinto, Ricardo da Silva Santos & Jose Maria Parente de Oliveira. (2014) Automatic and semantic pre — Selection of features using ontology for data mining on data sets related to cancer. Automatic and semantic pre — Selection of features using ontology for data mining on data sets related to cancer.
Shiuan Wan & Shih-Hsun Chang. (2014) Combined particle swarm optimization and linear discriminant analysis for landslide image classification: application to a case study in Taiwan. Environmental Earth Sciences 72:5, pages 1453-1464.
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P. S. V. S. Sai Prasad & C. Raghavendra Rao. 2014. Transactions on Rough Sets XVII. Transactions on Rough Sets XVII 82 108 .
Pradipta Maji & Sushmita PaulPradipta Maji & Sushmita Paul. 2014. Scalable Pattern Recognition Algorithms. Scalable Pattern Recognition Algorithms 105 129 .
Pradipta Maji & Sushmita PaulPradipta Maji & Sushmita Paul. 2014. Scalable Pattern Recognition Algorithms. Scalable Pattern Recognition Algorithms 1 42 .
Usman Qamar. (2013) A Rough-Set Feature Selection Model for Classification and Knowledge Discovery. A Rough-Set Feature Selection Model for Classification and Knowledge Discovery.
Nele Verbiest, Chris Cornelis & Francisco Herrera. (2013) FRPS: A Fuzzy Rough Prototype Selection method. Pattern Recognition 46:10, pages 2770-2782.
Crossref
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Crossref
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Crossref
P. S. V. S. Sai Prasad & C. Raghavendra Rao. (2013) Seed based fuzzy decision reduct for hybrid decision systems. Seed based fuzzy decision reduct for hybrid decision systems.
Yasuo Kudo & Tetsuya Murai. (2013) A Parallel Computation Method for Heuristic Attribute Reduction Using Reduced Decision Tables. Journal of Advanced Computational Intelligence and Intelligent Informatics 17:3, pages 371-376.
Crossref
Suresh Satapathy, Anima Naik & K. Parvathi. (2013) Rough set and teaching learning based optimization technique for optimal features selection. Open Computer Science 3:1.
Crossref
Zheng-Cai Lu, Zheng Qin, Qiao Jing & Lai-Xiang Shan. (2013) Positive Macroscopic Approximation for Fast Attribute Reduction. Journal of Applied Mathematics 2013, pages 1-11.
Crossref
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Mohammad Ali Bagheri, Qigang Gao & Sergio Escalera. (2012) Rough Set Subspace Error-Correcting Output Codes. Rough Set Subspace Error-Correcting Output Codes.
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Crossref
Sankar K. Pal, Saroj K. Meher & Soumitra Dutta. (2012) Class-dependent rough-fuzzy granular space, dispersion index and classification. Pattern Recognition 45:7, pages 2690-2707.
Crossref
Pradipta Maji & Sankar K. Pal. 2012. Rough‐Fuzzy Pattern Recognition. Rough‐Fuzzy Pattern Recognition 117 159 .
Pradipta Maji & Sankar K. Pal. 2012. Rough‐Fuzzy Pattern Recognition. Rough‐Fuzzy Pattern Recognition 85 116 .
Pradipta Maji & Sankar K. Pal. 2012. Rough‐Fuzzy Pattern Recognition. Rough‐Fuzzy Pattern Recognition 21 45 .
Li-Ye Zhang, Zhong-Ren PengDaniel (Jian) Sun & Xiaofeng Liu. (2012) Rule-Based Forecasting of Traffic Flow for Large-Scale Road Networks. Transportation Research Record: Journal of the Transportation Research Board 2279:1, pages 3-11.
Crossref
Sai Prasad P.S.V.S.Raghavendra Rao Chillarige. 2012. Multi-disciplinary Trends in Artificial Intelligence. Multi-disciplinary Trends in Artificial Intelligence 188 201 .
P. S. V. S. Sai Prasad & C. Raghavendra Rao. 2012. Rough Sets and Knowledge Technology. Rough Sets and Knowledge Technology 34 39 .
Pradipta Maji & Partha Garai. 2012. Advances on Computational Intelligence. Advances on Computational Intelligence 310 320 .
Zheng Liu, Liying Fang, Mingwei Yu, Pu Wang & Jianzhuo Yan. 2012. Intelligent Computing Technology. Intelligent Computing Technology 342 349 .
Moawia Elfaki Yahia. (2011) Arabic text categorization based on rough set classification. Arabic text categorization based on rough set classification.
Saroj K. Meher & Sankar K. Pal. (2011) Rough-wavelet granular space and classification of multispectral remote sensing image. Applied Soft Computing 11:8, pages 5662-5673.
Crossref
A. Q. Ansari. (2011) e - Document retrieval using rough-set theory. e - Document retrieval using rough-set theory.
Tsu-Chiang Lei, Shiuan Wan, Tien-Yin Chou & Hung-Chieh Pai. (2010) The knowledge expression on debris flow potential analysis through PCA + LDA and rough sets theory: a case study of Chen-Yu-Lan watershed, Nantou, Taiwan. Environmental Earth Sciences 63:5, pages 981-997.
Crossref
C. Thilagavathy & R. Rajesh. (2011) A note on rough set theory. A note on rough set theory.
Pradipta Maji & Sushmita Paul. (2011) Rough set based maximum relevance-maximum significance criterion and Gene selection from microarray data. International Journal of Approximate Reasoning 52:3, pages 408-426.
Crossref
. (2011) Heuristic Algorithm for Attribute Reduction Based on Classification Ability by Condition Attributes. Journal of Advanced Computational Intelligence and Intelligent Informatics 15:1, pages 102-109.
Crossref
Sai Prasad P.S.V.S.Chillarige Raghavendra Rao. 2011. Multi-disciplinary Trends in Artificial Intelligence. Multi-disciplinary Trends in Artificial Intelligence 351 362 .
P. S. V. S. Sai Prasad, K. Hima Bindu & C. Raghavendra Rao. 2011. Rough Sets and Knowledge Technology. Rough Sets and Knowledge Technology 195 200 .
Punam Bedi & Suruchi Chawla. 2011. Transactions on Rough Sets XIV. Transactions on Rough Sets XIV 18 36 .
Qiang Shen & Changjing Shang. 2011. Computational Intelligence. Computational Intelligence 23 41 .
S Paul & P Maji. (2010) Rough set based gene selection algorithm for microarray sample classification. Rough set based gene selection algorithm for microarray sample classification.
N. Mac Parthaláin & Q. Shen. (2010) On rough sets, their recent extensions and applications. The Knowledge Engineering Review 25:4, pages 365-395.
Crossref
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Crossref
Pradipta Maji & Sushmita Paul. (2010) Rough Sets for Selection of Molecular Descriptors to Predict Biological Activity of Molecules. IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews) 40:6, pages 639-648.
Crossref
Changseok Bae, Wei-Chang Yeh, Yuk Ying Chung & Sin-Long Liu. (2010) Feature selection with Intelligent Dynamic Swarm and Rough Set. Expert Systems with Applications 37:10, pages 7026-7032.
Crossref
Yasuo Kudo & Tetsuya Murai. (2010) An Attribute Reduction Algorithm by Switching Exhaustive and Heuristic Computation of Relative Reducts. An Attribute Reduction Algorithm by Switching Exhaustive and Heuristic Computation of Relative Reducts.
Richard Jensen, Andrew Tuson & Qiang Shen. (2010) Extending propositional satisfiability to determine minimal fuzzy-rough reducts. Extending propositional satisfiability to determine minimal fuzzy-rough reducts.
Ren Diao & Qiang Shen. (2010) Two new approaches to feature selection with harmony search. Two new approaches to feature selection with harmony search.
Pradipta Maji & Sankar K. Pal. (2010) Feature Selection Using f-Information Measures in Fuzzy Approximation Spaces. IEEE Transactions on Knowledge and Data Engineering 22:6, pages 854-867.
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Crossref
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P. S. V. S. Sai Prasad & C. Raghavendra Rao. 2009. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing. Rough Sets, Fuzzy Sets, Data Mining and Granular Computing 152 159 .
Agnieszka Maciocha & Jerzy Kisielnicki. 2009. Transactions on Rough Sets X. Transactions on Rough Sets X 169 196 .
Jiye Li & Nick Cercone. (2009) A method of discovering important rules using rules as attributes. International Journal of Intelligent Systems, pages n/a-n/a.
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Sombut Foitong, Phaitoon Srinil & Ouen Pinngern. (2008) Rough Sets Based Approach to Reduct Approximation: RSBARA. Rough Sets Based Approach to Reduct Approximation: RSBARA.
Richard Jensen & Qiang Shen. 2008. Computational Intelligence and Feature Selection. Computational Intelligence and Feature Selection 313 336 .
C.P. Chandran. (2008) Feature selection from protein primary sequence database using Enhanced QuickReduct Fuzzy-Rough set. Feature selection from protein primary sequence database using Enhanced QuickReduct Fuzzy-Rough set.
Abdel-Rahman Hedar, Jue Wang & Masao Fukushima. (2007) Tabu search for attribute reduction in rough set theory. Soft Computing 12:9, pages 909-918.
Crossref
Chris Cornelis & Richard Jensen. (2008) A noise-tolerant approach to fuzzy-rough feature selection. A noise-tolerant approach to fuzzy-rough feature selection.
Neil Mac Parthalain, Richard Jensen & Qiang Shen. (2008) Finding fuzzy-rough reducts with fuzzy entropy. Finding fuzzy-rough reducts with fuzzy entropy.
Changjing Shang & Qiang Shen. (2008) Aiding neural network based image classification with fuzzy-rough feature selection. Aiding neural network based image classification with fuzzy-rough feature selection.
Qiang Shen & Richard Jensen. (2007) Approximation-based feature selection and application for algae population estimation. Applied Intelligence 28:2, pages 167-181.
Crossref
Jeffrey L. Solka. (2008) Text Data Mining: Theory and Methods. Statistics Surveys 2:none.
Crossref
Farideh Fazayeli, Lipo Wang & Jacek Mandziuk. 2008. Rough Sets and Current Trends in Computing. Rough Sets and Current Trends in Computing 272 282 .
Shailendra Singh & Bhanu Prasad. 2008. Soft Computing Applications in Business. Soft Computing Applications in Business 147 178 .
Yaxin Bi, Xuhui Shen & Shengli Wu. 2008. Interval / Probabilistic Uncertainty and Non-Classical Logics. Interval / Probabilistic Uncertainty and Non-Classical Logics 187 200 .
Van-Nam Huynh, Tu-Bao Ho & Yoshiteru Nakamori. 2008. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models. Fuzzy Sets and Their Extensions: Representation, Aggregation and Models 493 515 .
A.Grace Selvarani & S. Annadurai. (2007) Medical Image Retrieval by Combining Low Level Features and DICOM Features. Medical Image Retrieval by Combining Low Level Features and DICOM Features.
. (2007) OWA Rough Set to Forecast the Industrial Growth Rate. OWA Rough Set to Forecast the Industrial Growth Rate.
Tien-Chin Wang, Lisa Y. Chen & Hsien-Da Lee. (2007) Fuzzy Entropy-Based Rough Set Approach for Extracting Decision Rules. Fuzzy Entropy-Based Rough Set Approach for Extracting Decision Rules.
Tien-Chin Wang, Hsien-Da Lee, Ta-Jen Yu & Ko Mei-Fei. (2007) Enhancing Fuzzy Rule Extraction Based on Rough Set Theory and Entropy. Enhancing Fuzzy Rule Extraction Based on Rough Set Theory and Entropy.
Fangtao Li, Tao Guan, Xian Zhang & Xiaoyan Zhu. (2007) An Aggressive Feature Selection Method based on Rough Set Theory. An Aggressive Feature Selection Method based on Rough Set Theory.
Qiang Shen & Richard Jensen. (2007) Rough sets, their extensions and applications. International Journal of Automation and Computing 4:3, pages 217-228.
Crossref
Neil Mac Parthalain, Qiang Shen & Richard Jensen. (2007) Distance Measure Assisted Rough Set Feature Selection. Distance Measure Assisted Rough Set Feature Selection.
Richard Jensen & Qiang Shen. (2007) Tolerance-based and Fuzzy-Rough Feature Selection. Tolerance-based and Fuzzy-Rough Feature Selection.
Xiangyang Wang, Jie Yang, Xiaolong Teng, Weijun Xia & Richard Jensen. (2007) Feature selection based on rough sets and particle swarm optimization. Pattern Recognition Letters 28:4, pages 459-471.
Crossref
Richard Jensen & Qiang Shen. (2007) Fuzzy-Rough Sets Assisted Attribute Selection. IEEE Transactions on Fuzzy Systems 15:1, pages 73-89.
Crossref
Jiye Li, Puntip Pattaraintakorn & Nick Cercone. 2007. Transactions on Rough Sets VI. Transactions on Rough Sets VI 152 171 .
Yaxin Bi, Sally McClean & Terry Anderson. (2007) Combining rough decisions for intelligent text mining using Dempster’s rule. Artificial Intelligence Review 26:3, pages 191-209.
Crossref
Ying-Chieh Tsai, Ching-Hsue Cheng & Jing-Rong Chang. (2006) Entropy-based fuzzy rough classification approach for extracting classification rules. Expert Systems with Applications 31:2, pages 436-443.
Crossref
Y. Li, S.C.K. Shiu, S.K. Pal & J.N.K. Liu. (2006) A rough set-based case-based reasoner for text categorization. International Journal of Approximate Reasoning 41:2, pages 229-255.
Crossref
Neil Mac Parthalain, R. Jensen & Qiang Shen. (2006) Fuzzy Entropy-assisted Fuzzy-Rough Feature Selection. Fuzzy Entropy-assisted Fuzzy-Rough Feature Selection.
Richard Jensen. 2006. Swarm Intelligence in Data Mining. Swarm Intelligence in Data Mining 45 73 .
Richard Jensen & Qiang Shen. 2006. Rough Sets and Current Trends in Computing. Rough Sets and Current Trends in Computing 147 156 .
Kalyan Moy Gupta, David W. Aha & Philip Moore. 2006. Advances in Case-Based Reasoning. Advances in Case-Based Reasoning 166 181 .
Mao Ye, Boqin Feng, Li Zhu & Yao Lin. 2006. Rough Sets and Knowledge Technology. Rough Sets and Knowledge Technology 786 791 .
Shailendra Singh & Lipika Dey. (2005) A new customized document categorization scheme using rough membership. Applied Soft Computing 5:4, pages 373-390.
Crossref
Shailendra Singh & Lipika Dey. (2005) A rough-fuzzy document grading system for customized text information retrieval. Information Processing & Management 41:2, pages 195-216.
Crossref
Richard Jensen & Qiang Shen. (2005) Fuzzy-rough data reduction with ant colony optimization. Fuzzy Sets and Systems 149:1, pages 5-20.
Crossref
Qiang Li & Jianhua Li. 2005. Web Technologies Research and Development - APWeb 2005. Web Technologies Research and Development - APWeb 2005 157 163 .
Kalyan Moy Gupta, Philip G. Moore, David W. Aha & Sankar K. Pal. 2005. Pattern Recognition and Machine Intelligence. Pattern Recognition and Machine Intelligence 792 798 .
Xiangyang Wang, Jie Yang, Ningsong Peng & Xiaolong Teng. 2005. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 451 460 .
Richard Jensen, Qiang Shen & Andrew Tuson. 2005. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing. Rough Sets, Fuzzy Sets, Data Mining, and Granular Computing 194 203 .
Qiang Li & Jianhua Li. 2005. Autonomous Intelligent Systems: Agents and Data Mining. Autonomous Intelligent Systems: Agents and Data Mining 175 183 .
R. Jensen & Q. Shen. (2004) Semantics-preserving dimensionality reduction: rough and fuzzy-rough-based approaches. IEEE Transactions on Knowledge and Data Engineering 16:12, pages 1457-1471.
Crossref
Chengdong Wu, Yong Yue, Mengxin Li & Osei Adjei. (2004) The rough set theory and applications. Engineering Computations 21:5, pages 488-511.
Crossref
T. Wakaki, H. Itakura & M. Tamura. (2004) Rough Set-Aided Feature Selection for Automatic Web-Page Classification. Rough Set-Aided Feature Selection for Automatic Web-Page Classification.
Yan Li, S.C.-K. Shiu, S.K. Pal & J.N.-K. Liu. (2004) A rough set-based CBR approach for feature and document reduction in text categorization. A rough set-based CBR approach for feature and document reduction in text categorization.
Qiang Li, Jian-Hua Li, Gong-Shen Liu & Sheng-Hong Li. (2004) A rough set-based hybrid feature selection method for topic-specific text filtering. A rough set-based hybrid feature selection method for topic-specific text filtering.
Qiang Shen. 2003. Modelling with Words. Modelling with Words 64 79 .
Shailendra Singh, P. Dhanalakshmi & Lipika Dey. 2003. Advances in Web Intelligence. Advances in Web Intelligence 258 267 .
Qiang Shen & A. Chouchoulas. (2001) Selection of features in transparent fuzzy modelling. Selection of features in transparent fuzzy modelling.
Richard Jensen & Qiang Shen. 2001. Web Intelligence: Research and Development. Web Intelligence: Research and Development 95 105 .

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