12. RSFDGrC 2009: Delhi, India

Plenary Papers and Reports

• Ivo Düntsch, Günther Gediga, Adam Lenarcic:
  Affordance Relations. 1-11
  
• Zbigniew Suraj:
  Discovering Concurrent Process Models in Data: A Rough Set Approach. 12-19
  
• Zhongzhi Shi:
  Intelligent Science. 20-32
  
• Sergei O. Kuznetsov:
  Pattern Structures for Analyzing Complex Data. 33-44
  
• Qiang Shen:
  Fuzzy Sets and Rough Sets for Scenario Modelling and Analysis. 45-58
  
• Yukio Ohsawa:
  Innovation Game as a Tool of Chance Discovery. 59-66
  
• Manish Joshi, Rabi N. Bhaumik, Pawan Lingras, Nitin Patil, Ambuja Salgaonkar, Dominik Slezak:
  Rough Set Year in India 2009. 67-68
  

Foundations of Rough Sets and Beyond

• Md. Aquil Khan, Mohua Banerjee:
  An Algebraic Semantics for the Logic of Multiple-Source Approximation Systems. 69-76
  
• A. Mani:
  Towards an Algebraic Approach for Cover Based Rough Semantics and Combinations of Approximation Spaces. 77-84
  
• E. K. R. Nagarajan, D. Umadevi:
  New Approach in Defining Rough Approximations. 85-92
  
• Wei-Zhi Wu:
  Rough Set Approximations Based on Granular Labels. 93-100
  
• Yasuo Kudo, Tetsuya Murai:
  On a Criterion of Similarity between Partitions Based on Rough Set Theory. 101-108
  
• Ryszard Janicki:
  On Rough Sets with Structures and Properties. 109-116
  
• Bernhard Ganter, Christian Meschke:
  A Formal Concept Analysis Approach to Rough Data Tables. 117-126
  
• Pulak Samanta, Mihir K. Chakraborty:
  Covering Based Approaches to Rough Sets and Implication Lattices. 127-134
  
• Kazumi Nakamatsu, Jair Minoro Abe, Seiki Akama:
  A Logical Reasoning System of Before-after Relation Based on Bf-EVALPSN. 135-143
  
• Soma Dutta, Mihir K. Chakraborty:
  Some Proof Theoretic Results Depending on Context from the Perspective of Graded Consequence. 144-151
  

Rough Set Algorithms and Applications

• P. S. V. S. Sai Prasad, C. Raghavendra Rao:
  IQuickReduct: An Improvement to Quick Reduct Algorithm. 152-159
  
• Salsabil Trabelsi, Zied Elouedi, Pawan Lingras:
  Dynamic Reduct from Partially Uncertain Data Using Rough Sets. 160-167
  
• Marcin S. Szczuka:
  Approximation of Loss and Risk in Selected Granular Systems. 168-175
  
• Na Jiao, Duoqian Miao:
  An Efficient Gene Selection Algorithm Based on Tolerance Rough Set Theory. 176-183
  
• Santosh Kumar Ray, Shailendra Singh:
  Rough Set Based Social Networking Framework to Retrieve User-Centric Information. 184-191
  
• Punam Bedi, Suruchi Chawla:
  Use of Fuzzy Rough Set Attribute Reduction in High Scent Web Page Recommendations. 192-200
  
• Daryl H. Hepting, Timothy Maciag, Richard Spring, Katherine Arbuthnott, Dominik Slezak:
  A Rough Sets Approach for Personalized Support of Face Recognition. 201-208
  
• Changjing Shang, Dave Barnes, Qiang Shen:
  Taking Fuzzy-Rough Application to Mars. 209-216
  
• Gerald Schaefer, Huiyu Zhou, Qinghua Hu, Aboul Ella Hassanien:
  Rough Image Colour Quantisation. 217-222
  
• Mohamed Elhadi, Amjad Al-Tobi:
  Part of Speech (POS) Tag Sets Reduction and Analysis Using Rough Set Techniques. 223-230
  

Fuzzy Set Foundations and Applications

• Pabitra Kumar Maji:
  More on Intuitionistic Fuzzy Soft Sets. 231-240
  
• M. Parimala, R. Devi:
  On Fuzzy Contra alpha-Irresolute Maps. 241-246
  
• A. Selvakumar, R. Devi:
  On Fuzzy Strongly alpha-I-Open Sets. 247-252
  
• Guilong Liu:
  Lattice Structures of Rough Fuzzy Sets. 253-260
  
• B. Praba, R. Sujatha, V. Hilda Christy Gnanam:
  Analysis of Ergodicity of a Fuzzy Possibilistic Markov Model. 261-268
  
• Junzo Watada, Lee-Chuan Lin, Minji Qiang, Pei-Chun Lin:
  A Fuzzy Random Variable Approach to Restructuring of Rough Sets through Statistical Test. 269-277
  
• Amit Kumar, Neha Bhatia, Manjot Kaur:
  A New Approach for Solving Fuzzy Maximal Flow Problems. 278-286
  
• Sanchita Paul, Abhimanyu K. Singh, Gadhadhar Sahoo:
  Peptic Ulcer Detection Using DNA Nanorobot Based on Fuzzy Logic Rules. 287-294
  
• Vishram B. Sawant, Suhas S. Mohite:
  Investigations on Benefits Generated By Using Fuzzy Numbers in A TOPSIS Model Developed For Automated Guided Vehicle Selection Problem. 295-302
  
• Kavita, Shiv Prasad Yadav, Surendra Kumar:
  A Multi-criteria Interval-Valued Intuitionistic Fuzzy Group Decision Making for Supplier Selection with TOPSIS Method. 303-312
  

Data Mining and Knowledge Discovery

• Hiroshi Sakai, Kohei Hayashi, Michinori Nakata, Dominik Slezak:
  The Lower System, the Upper System and Rules with Stability Factor in Non-deterministic Information Systems. 313-320
  
• Peter H. F. Ng, Simon C. K. Shiu, Haibo Wang:
  Learning Player Behaviors in Real Time Strategy Games from Real Data. 321-327
  
• Veena H. Bhat, Prasanth G. Rao, P. Deepa Shenoy, K. R. Venugopal, Lalit M. Patnaik:
  An Efficient Prediction Model for Diabetic Database Using Soft Computing Techniques. 328-335
  
• Hui-Ming Wee, Jie Lu, Guangquan Zhang, Huai-En Chiao, Ya Gao:
  A Decision Making Model for Vendor-Buyer Inventory Systems. 336-343
  
• Ramakanta Mohanty, V. Ravi, Manas Ranjan Patra:
  Software Reliability Prediction Using Group Method of Data Handling. 344-351
  
• Upasna Singh, Kevindra Pal Singh, Gora Chand Nandi:
  Mining Temporal Patterns for Humanoid Robot Using Pattern Growth Method. 352-360
  
• Shoji Hirano, Shusaku Tsumoto:
  Multiscale Comparison of Three-Dimensional Trajectories: A Preliminary Step. 361-368
  
• Arindam Chaudhuri, Kajal De:
  Time Series Forecasting Using Hybrid Neuro-Fuzzy Regression Model. 369-381
  
• Ying Zhang, Xizhao Wang, Junhai Zhai:
  A Fast Support Vector Machine Classification Algorithm Based on Karush-Kuhn-Tucker Conditions. 382-389
  
• M. A. H. Farquad, V. Ravi, S. Bapi Raju:
  Data Mining Using Rules Extracted from SVM: An Application to Churn Prediction in Bank Credit Cards. 390-397
  

Clustering and Current Trends in Computing

• Yiyu Yao, Pawan Lingras, Ruizhi Wang, Duoqian Miao:
  Interval Set Cluster Analysis: A Re-formulation. 398-405
  
• Dariusz Malyszko, Jaroslaw Stepaniuk:
  Rough Entropy Based k-Means Clustering. 406-413
  
• Bidyut Kr. Patra, Sukumar Nandi:
  Fast Single-Link Clustering Method Based on Tolerance Rough Set Model. 414-422
  
• Hong Yu, Hu Luo:
  A Novel Possibilistic Fuzzy Leader Clustering Algorithm. 423-430
  
• Naveen Kumar, Charu Puri:
  Projected Gustafson Kessel Clustering. 431-438
  
• K. Thangavel, P. Alagambigai, D. Devakumari:
  Improved Visual Clustering through Unsupervised Dimensionality Reduction. 439-446
  
• Shan Su, Xizhao Wang, Junhai Zhai:
  An Improved Cluster Oriented Fuzzy Decision Trees. 447-454
  
• S. Thamaraiselvi, R. Srivathsan, J. Imayavendhan, Raghavan Muthuregunathan, S. Siddharth:
  Combining Naive-Bayesian Classifier and Genetic Clustering for Effective Anomaly Based Intrusion Detection. 455-462
  
• Gerald Schaefer:
  Ant Colony Optimisation Classification for Gene Expression Data Analysis. 463-469
  
• G. Jeyakumar, C. Shunmuga Velayutham:
  A Comparative Performance Analysis of Multiple Trial Vectors Differential Evolution and Classical Differential Evolution Variants. 470-477
  

Information Retrieval and Text Mining

• Liping Jing, Raymond Y. K. Lau:
  Granular Computing for Text Mining: New Research Challenges and Opportunities. 478-485
  
• Ashish Sureka, Vikram Goyal, Denzil Correa, Anirban Mondal:
  Polarity Classification of Subjective Words Using Common-Sense Knowledge-Base. 486-493
  
• Arijit De, Elizabeth D. Diaz:
  A Weighted Hybrid Fuzzy Result Merging Model for Metasearch. 494-501
  
• Hidenao Abe, Shusaku Tsumoto:
  Comparing Temporal Behavior of Phrases on Multiple Indexes with a Burst Word Detection Method. 502-509
  
• Fan Min, Xindong Wu:
  A Comparative Study of Pattern Matching Algorithms on Sequences. 510-517
  
• Xiao-Li Hong, Xindong Wu, Xuegang Hu, Ying-Ling Liu, Jun Gao, Gong-Qing Wu:
  BPBM: An Algorithm for String Matching with Wildcards and Length Constraints. 518-525
  

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