Data Mining: Foundations and Practice 2008

• Elena Baralis, Silvia Chiusano, Riccardo Dutto, Luigi Mantellini:
  Compact Representations of Sequential Classification Rules. 1-30
  
• Haiyun Bian, Raj Bhatnagar:
  An Algorithm for Mining Weighted Dense Maximal 1-Complete Regions. 31-48
  
• Chun-Hao Chen, Tzung-Pei Hong, Vincent S. Tseng:
  Mining Linguistic Trends from Time Series. 49-60
  
• I-Jen Chiang, Tsau Young Lin, Ginni Hsiang-Chun Tsai, Jau-Min Wong, Xiaohua Hu:
  Latent Semantic Space for Web Clustering. 61-77
  
• David Corney, Emma Byrne, Bernard Buxton, David Jones:
  A Logical Framework for Template Creation and Information Extraction. 79-108
  
• Tuan-Fang Fan, Churn-Jung Liau, Duen-Ren Liu:
  A Bipolar Interpretation of Fuzzy Decision Trees. 109-123
  
• Qing Shi Gao, Xiao Yu Gao, Lei Xu:
  A Probability Theory Perspective on the Zadeh Fuzzy System. 125-137
  
• Jerzy W. Grzymala-Busse:
  Three Approaches to Missing Attribute Values: A Rough Set Perspective. 139-152
  
• Jerzy W. Grzymala-Busse:
  MLEM2 Rule Induction Algorithms: With and Without Merging Intervals. 153-164
  
• P. González-Aranda, Ernestina Menasalvas Ruiz, Socorro Millán, Carlos Ruiz, Javier Segovia:
  Towards a Methodology for Data Mining Project Development: The Importance of Abstraction. 165-178
  
• Tzung-Pei Hong, Chun-Hao Chen, Yu-Lung Wu, Vincent S. Tseng:
  Fining Active Membership Functions in Fuzzy Data Mining. 179-196
  
• José Hernández Palancar, Raudel Hernández-León, José E. Medina-Pagola, Abdel Hechavarría Díaz:
  A Compressed Vertical Binary Algorithm for Mining Frequent Patterns. 197-211
  
• Lawrence J. Mazlack:
  Naïve Rules Do Not Consider Underlying Causality. 213-229
  
• Lawrence J. Mazlack:
  Inexact Multiple-Grained Causal Complexes. 231-249
  
• Mykola Pechenizkiy, Seppo Puuronen, Alexey Tsymbal:
  Does Relevance Matter to Data Mining Research?. 251-275
  
• Li-Shiang Tsay, Zbigniew W. Ras:
  E-Action Rules. 277-288
  
• Zbigniew W. Ras, Li-Shiang Tsay:
  Mining E-Action Rules, System DEAR. 289-298
  
• Jan Rauch:
  Classes of Association Rules: An Overview. 315-337
  
• Gregor Stiglic, Nawaz Khan, Peter Kokol:
  Knowledge Extraction from Microarray Datasets Using Combined Multiple Models to Predict Leukemia Types. 339-352
  
• Bhavani M. Thuraisingham:
  On the Complexity of the Privacy Problem in Databases. 353-374
  
• Kari Torkkola, Eugene Tuv:
  Ensembles of Least Squares Classifiers with Randomized Kernels. 375-386
  
• Shusaku Tsumoto:
  On Pseudo-Statistical Independence in a Contingency Table. 387-403
  
• Shusaku Tsumoto:
  Role of Sample Size and Determinants in Granularity of Contingency Matrix. 405-421
  
• Bob Wall, Neal Richter, Rafal A. Angryk:
  Generating Concept Hierarchies from User Queries. 423-441
  
• Yanbo J. Wang, Qin Xin, Frans Coenen:
  Mining Efficiently Significant Classification Association Rules. 443-467
  
• Anita Wasilewska, Ernestina Menasalvas Ruiz:
  Data Preprocessing and Data Mining as Generalization. 469-484
  
• Yiyu Yao, Ning Zhong, Yan Zhao:
  A Conceptual Framework of Data Mining. 501-515
  
• Justin Z. Zhan, LiWu Chang, Stan Matwin:
  How to Prevent Private Data from being Disclosed to a Malicious Attacker. 517-528
  
• Justin Z. Zhan, Stan Matwin, LiWu Chang:
  Privacy-Preserving Naive Bayesian Classification over Horizontally Partitioned Data. 529-538
  
• S. P. Subasingha, J. Zhang, Kamal Premaratne, Mei-Ling Shyu, Miroslav Kubat, K. K. Rohitha Hewawasam:
  Using Association Rules for Classification from Databases Having Class Label Ambiguities: A Belief Theoretic Method. 539-562
  

Last update Wed Feb 15 04:52:38 2012 CET by the DBLP Team — Data released under the ODC-BY 1.0 license — See also our legal information page