Table of Contents

• Default ARTMAP Neural Networks for Financial DiagnosisAnatoli Nachev, Borislav Stoyanov. 3-9
• Time Series Prediction with Parallel Evolutionary Artificial Neural NetworksKristina Davoian, Wolfram-Manfred Lippe. 10-15
• Finding Associations in Time Series Data Using CentroidsDurga Toshniwal, Ramesh C. Joshi. 16-21
• Mining Data for Profitable TradingB. Chandra, P. Paul Varghese, Ashok Wardhan. 22-30
• Pre-Extracting Boundary Samples for SVM Based on Perpendicular Bisector Distance MethodLili Cheng, Jianpei Zhang, Jing Yang, Jun Ma. 31-34
• Cost-Sensitive Learning vs. Sampling: Which is Best for Handling Unbalanced Classes with Unequal Error Costs?Gary M. Weiss, Kate McCarthy, Bibi Zabar. 35-41
• Using Partial Least Squares in ClassificationAlbert Hoang. 42-45
• A Fast KNN Algorithm Based on Simulated AnnealingChuanyao Yang, Yuqin Li, Chenghong Zhang, Yunfa Hu. 46-51
• Construct Optimal Predictive Classificatoin rulesMohammad Naderi Dehkordi, Mohammad Hassan Shenassa. 52-58
• Towards a Unified View on Concept DescriptionCecilia Sönströd, Ulf Johansson, Rikard König. 59-65
• Generative Oversampling for Mining Imbalanced DatasetsAlexander Liu, Joydeep Ghosh, Cheryl Martin. 66-72
• Instance Ranking using Ensemble SpreadRikard König, Ulf Johansson, Lars Niklasson. 73-78
• Comparing the Results of Support Vector Machines with Traditional Data Mining AlgorithmsScott Pion, Lutz Hamel. 79-83
• Local Selective Partitioning for Heterogeneous Classification ProblemsIryna Skrypnyk. 84-90
• On 0-1 LearningXiyi Hang. 91-98
• On Clustering Users Behaviors in Video SessionsSylvain Mongy, Chabane Djeraba, Dan A. Simovici. 99-103
• A Novel Cluster Center Estimation Algorithm with Hybrid Partitional ClusteringLi-Tung Weng, Yue Xu, Yuefeng Li, Richi Nayak. 104-110
• Variance-based Clustering Technique for Distributed Data Mining ApplicationsLamine M. Aouad, Nhien-An Le-Khac, M. Tahar Kechadi. 111-117
• Clustering Approach for Fissuring Forrester s EffectDanish Irfan, Xiaofei Xu, Shengchun Deng, H. K. Sulehria. 118-126
• Towards Average Case Analysis of Itemset MiningDan Singer, David J. Haglin, Anna M. Manning. 127-133
• Updating Technique for Association Rules in Incremental DatabasesSonal Dekhane. 134-140
• On Minimal Infrequent Itemset MiningDavid J. Haglin, Anna M. Manning. 141-147
• Mining Frequent Itemsets Using Re-Usable Data StructureMohamed Yakout, Alaaeldin M. Hafez, Hussein Aly. 148-155
• PSFIT: An Efficient Algorithm for Mining Closed Frequent PatternsChuanyao Yang, Yuqin Li, Chenghong Zhang, Yunfa Hu. 156-162
• A Study of the Robustness of Association RulesJérôme Azé, Philippe Lenca, Stéphane Lallich, Benoît Vaillant. 163-169
• ITR: An Improved Algorithm For Mining Frequent ItemsetsArchana Raghavendran, John Thomas Selvaraj, Dawood Mohamed Imran. 170-178
• Evaluating Database Marketing Models: More than Meets the EyeSam Koslowsky. 179-182
• Crawling Attacks Against Web-based Recommender SystemsRuna Bhaumik, Robin D. Burke, Bamshad Mobasher. 183-189
• Finding the Positive Nearest-Neighbor in Recommender SystemsAli M. Roumani, David B. Skillicorn. 190-196
• Evaluating Retail Recommender Systems via Retrospective Data: Lessons Learnt from a Live-Intervention StudyCarmen M. Sordo-Garcia, M. Benjamin Dias, Ming Li, Wael El-Deredy, Paulo J. G. Lisboa. 197-206
• An Examination of Features for Expert Team Formation via Social Network AnalysisMichelle Cheatham, Felicia Harlow, Kevin Cleereman. 207-213
• Applications of Data mining in a Web-enabled Caregiver-Report Tool for Symptom Relations in DementiaPeter Zhang, Kenneth Rockwood, Arnold Mitnitski. 214-220
• Knowledge Discovery using Artificial Neural Networks for a Conservation Biology DomainRohitash Chandra, Christian W. Omlin. 221-227
• Improving the Performance of Gene Mention Recognition System using Reformed Lexicon-based Support Vector MachineYifei Chen, Feng Liu, Bernard Manderick. 228-234
• Validating HODA with Classical Clustering Techniques using Microarray Gene Expression DataMohammed Essam Khalifa, Taysir Hassan A. Soliman, Huda Amin Maghawry. 235-241
• A Survey of Frequent Pattern Mining for Biological DatasetsXuequn Shang. 242-248
• Treatment Outcome for Patients with Low Back InjuriesRichard J. Roiger, Mark Miller, Julie Morgan, Faye Hudson. 249-255
• Evaluation of Feature Selection Techniques for Analysis of Functional MRI and EEGLauren Burrell, Otis Smart, George Georgoulas, Eric Marsh, George Vachtsevanos. 256-262
• Structurally Evolved Neural Networks for Malignancy ClassificationAngelos Molfetas, George Bryan. 263-272
• Efficient Parallel Computation of Inverse Document Frequency Features for Text MiningJohn Rushing, Todd Berendes, Sara Graves. 273-278
• TIC: Term Intersection Clustering AlgorithmCasey Bartman, Jamal R. Alsabbagh. 279-284
• Efficient Summarization Based On Categorized KeywordsChristos Bouras, Vassilis Poulopoulos, Vassilis Tsogkas. 285-291
• The Internet Democracy: A Predictive Model Based on Web Text MiningScott Pion, Lutz Hamel. 292-300
• Privacy Preserving in Clustering by Categorizing Attributes Using Privacy and Non Privacy Disclosure SetsSridevi Kilambi, K. V. S. V. N. Raju, Valli Kumari Vatsavayi, SrinivasaRao Siringi. 301-307
• Privacy Preserving CACTUS Algorithm for Clustering over Vertically Partitioned DatabasesP. Krishna Prasad, C. Pandu Rangan. 308-314
• Synthetic Data for Privacy Preserving Data MiningVishal Pannala, Sibesh Bhattacharya, Ashutosh Saxena. 315-320
• A Clustering Approach for Achieving Data PrivacyAlina Campan, Traian Marius Truta, John Miller, Raluca Sinca. 321-330
• Neural Network Based Missing Data Recovery For Crash DatabaseAhmet Tan, Osman Kandara, Omer Soysal, Helmut Schneider. 331-337
• Dimensionality Reduction and Variable SelectionAnthony J. Grichnik, Michael Seskin. 338-342
• Toward Database Semantic Integration - An Approach Based on Conceptual Schema Inference and OntologyTouraj Varaee, Mohammad Hassan Shenassa, Amir Masoud Rahmani. 343-349
• A Multiple Level Sequential Pattern Mining Model over Data StreamHaifeng Li, Hong Chen. 350-343
• A Web Mining Usage based on Degree of Concern with Locational Information ContentsZu Kang, Bong Joon Choi, Kyoo Seok Park. 354-358
• A knowledge-based methodology to predict performance order of data-dependent applicationsPaula Cecilia Fritzsche, Dolores Rexachs, Emilio Luque. 359-368
• Graph Clustering Evaluation via Integer Linear ProgrammingYiming Yao, Tracy Hickling, William G. Hanley, Jason Lenderman. 369-375
• Mining for Structural Anomalies in Graph-based DataWilliam Eberle, Lawrence B. Holder. 376-389
• Image Mining: a ReviewJacqueline Fernández, Natalia Miranda, Roberto Guerrero, Fabiana Piccoli. 383-389
• Attribute Ordering and Inversion Algorithms for Parallel CoordinatesChunyu Yang, Jie Zhou. 390-396
• Enabling the Messmer s Graph Decomposition Approach for Subgraph Isomorphism Detection to Apply to a Larger Set of GraphsTakayoshi Fuse, Shotaro Nishimura, Kaoru Kayayama. 397-403
• Data Mining of Modulation Features Using Higher-Order Statistical Transform for Battlefield AwarenessWei Su, John A. Kosinski. 404-408
• Modifying a Simplified EM Algorithm for Text Clustering using a SM based Operation on String VectorsTaeho Jo, Malrey Lee, Hyogun Yoon, Chulgyu Song. 409-413
• Support for Mining Alert Patterns from Data StreamsRichard A. Wasniowski. 414-417
• Sales Forecasting Using Structural Risk Minimization Principle of Statistical Learning TheoryHafiz Muhammad Shahzad Asif, Muhammad Adam Mohyuddin, Muhammad Shahbaz. 418