Table of Contents

• Tutorial CIDM-T Temporal pattern mining in symbolic time point and time interval dataFabian Mörchen. [doi]
• Building ultra-low false alarm rate Support Vector Classifier ensembles using Random SubspacesBarry Chen, Tracy D. Lemmond, William G. Hanley. 1-8 [doi]
• Collaborative filtering with fine-grained trust metricSu Chen, Tiejian Luo, Wei Liu, Yanxiang Xu. 9-16 [doi]
• HybridSOM: A generic rule extraction framework for self-organizing feature mapsWillem S. van Heerden, Andries Petrus Engelbrecht. 17-24 [doi]
• Assessing the influence probability between objects: A random walker approachPei Li, Zhixu Li, Jun He, Xiaoyong Du, Hongyan Liu. 25-32 [doi]
• Intelligent feature extraction and knowledge mining by multivariate analysesYisong Chen, Hong Cui. 33-39 [doi]
• Efficient model selection for Support Vector Machine with Gaussian kernel functionYaohua Tang, Weimin Guo, Jinghuai Gao. 40-45 [doi]
• A fault tolerant peer-to-peer distributed EM algorithmBehrooz Safarinejadian, Mohammad B. Menhaj, Mehdi Karrari. 46-52 [doi]
• A new hybrid method for Bayesian network learning With dependency constraintsOliver Schulte, Gustavo Frigo, Russell Greiner, Wei Luo, Hassan Khosravi. 53-60 [doi]
• A pillar algorithm for K-means optimization by distance maximization for initial centroid designationAli Ridho Barakbah, Yasushi Kiyoki. 61-68 [doi]
• An adaptive ensemble classifier for concept drifting streamDengyuan Wu, Ying Liu, Ge Gao, Zhendong Mao, Weishan Ma, Tao He. 69-75 [doi]
• Missing traffic flow data prediction using least squares support vector machines in urban arterial streetsYang Zhang, Yuncai Liu. 76-83 [doi]
• Dynamic classifier selection using clustering for spam detectionMehrnoush Famil Saeedian, Hamid Beigy. 84-88 [doi]
• Skill rating by Bayesian inferenceGiuseppe Di Fatta, G. McC. Haworth, Kenneth W. Regan. 89-94 [doi]
• Clustering-based activity classification with a wrist-worn accelerometer using basic featuresPekka Siirtola, Perttu Laurinen, Eija Haapalainen, Juha Röning, Hannu Kinnunen. 95-100 [doi]
• Decision trees as information source for attribute selectionKyoko Fukuda, Brent Martin. 101-108 [doi]
• An enhanced data mining life cycleMarkus Hofmann, Brendan Tierney. 109-117 [doi]
• Local mining of Association Rules with Rule SchemasAndrei Olaru, Claudia Marinica, Fabrice Guillet. 118-124 [doi]
• Extracting hot spots of basic and complex topics from time stamped documentsWei Chen, Parvathi Chundi. 125-132 [doi]
• Hierarchically classifying documents with multiple labelsAndrew Mayne, Russell Perry. 133-139 [doi]
• Determining the strength of the propensities of a blog networkSeok-Ho Yoon, Sang-Wook Kim, Sunju Park. 140-145 [doi]
• Mining electronic medical records for patient care patternsAnna L. Buczak, Linda J. Moniz, Brian H. Feighner, Joseph S. Lombardo. 146-153 [doi]
• Gender identification from E-mailsNa Cheng, Xiaoling Chen, R. Chandramouli, K. P. Subbalakshmi. 154-158 [doi]
• Generalized random rotation perturbation for vertically partitioned data setsZhenmin Lin, Jie Wang, Lian Liu, Jun Zhang. 159-162 [doi]
• Mining for insider threats in business transactions and processesWilliam Eberle, Lawrence B. Holder. 163-170 [doi]
• Density-based clustering of polygonsDeepti Joshi, Ashok Samal, Leen-Kiat Soh. 171-178 [doi]
• Non-collaborative interest mining for personal devicesSangoh Jeong, Doreen Cheng, Henry Song, Swaroop Kalasapur. 179-186 [doi]
• An empirical study of bagging and boosting ensembles for identifying faulty classes in object-oriented softwareHamoud I. Aljamaan, Mahmoud O. Elish. 187-194 [doi]
• Automatic analysis of eye tracking data for medical diagnosisFilippo Galgani, Yiwen Sun, Pier Luca Lanzi, Jason Leigh. 195-202 [doi]
• Application of the preference learning model to a human resources selection taskFabio Aiolli, Michele De Filippo, Alessandro Sperduti. 203-210 [doi]
• Practical fuzzy decision treesNa el Abu-halaweh, Robert Harrison. 211-216 [doi]
• Data mining via protoform based linguistic summaries: Some possible relations to natural language generationJanusz Kacprzyk, Slawomir Zadrozny. 217-224 [doi]
• Handling continuous attributes in Ant Colony Classification algorithmsFernando E. B. Otero, Alex Alves Freitas, Colin G. Johnson. 225-231 [doi]
• A novel data clustering algorithm based on electrostatic field conceptsMasoumeh Kalantari Khandani, Parvaneh Saeedi, Yaser P. Fallah, Mehdi K. Khandani. 232-237 [doi]
• Evolving decision trees using oracle guidesUlf Johansson, Lars Niklasson. 238-244 [doi]
• Ensemble member selection using multi-objective optimizationTuve Löfström, Ulf Johansson, Henrik Boström. 245-251 [doi]
• Association based classification for relational data and its use in web miningVladimír Bartik. 252-258 [doi]
• Empirical comparison of graph classification algorithmsNikhil S. Ketkar, Lawrence B. Holder, Diane J. Cook. 259-266 [doi]
• Faster computation of the direct product kernel for graph classificationNikhil S. Ketkar, Lawrence B. Holder, Diane J. Cook. 267-274 [doi]
• Dependable performance analysis for fuzzy clustering of web usage dataAmir Ketata, Sudhir P. Mudur, Nematollaah Shiri. 275-282 [doi]
• Discovering relational knowledge from two disjoint sets of literatures using inductive Logic ProgrammingSupphachai Thaicharoen, Tom Altman, Katheleen J. Gardiner, Krzysztof J. Cios. 283-290 [doi]
• LD-BSCA: A local-density based spatial clustering algorithmGuiyi Wei, Haiping Liu. 291-298 [doi]
• Trajectory clustering in road network environmentJung-Im Won, Sang-Wook Kim, Ji-Haeng Baek, Junghoon Lee. 299-305 [doi]
• An architecture and algorithms for multi-run clusteringRachsuda Jiamthapthaksin, Christoph F. Eick, Vadeerat Rinsurongkawong. 306-313 [doi]
• MWASP: Multiple-Width Approximate Sequential PatternsKelly Kingchi Yip, David A. Nembhard. 314-319 [doi]
• Fuzzy p-mode prototypes: A generalization of frequency-based cluster prototypes for clustering categorical objectsMahnhoon Lee. 320-323 [doi]
• Diversity analysis on imbalanced data sets by using ensemble modelsShuo Wang, Xin Yao. 324-331 [doi]
• Large-scale attribute selection using wrappersMartin Gutlein, Eibe Frank, Mark Hall, Andreas Karwath. 332-339 [doi]
• An improved multiple minimum support based approach to mine rare association rulesR. Uday Kiran, P. Krishna Reddy. 340-347 [doi]
• Data mining with ensembles of fuzzy decision treesChristophe Marsala. 348-354 [doi]
• The locality of RBF-SVM for incremental learningWael Emara, Mehmed M. Kantardzic. 355-362 [doi]
• Parametric subspace analysis for dimensionality reduction and classificationNhat Vo, Duc Vo, Subhash Challa, Bill Moran. 363-366 [doi]
• Incremental Wrapper-based subset Selection with replacement: An advantageous alternative to sequential forward selectionPablo Bermejo, José A. Gámez, Jose Miguel Puerta. 367-374 [doi]
• Analysis and visualization of the geographical distribution of atlantic forest bromeliads speciesStainam N. Brandao, Wagner N. Silva, Luis A. E. Silva, Vladimir Fagundes, Carlos Eduardo R. de Mello, Geraldo Zimbrão, Jano Moreira de Souza. 375-380 [doi]
• Maintaining only frequent itemsets to mine approximate frequent itemsets over online data streamsYongyan Wang, Kun Li, Hongan Wang. 381-388 [doi]
• Regularized Extreme Learning MachineWanyu Deng, Qinghua Zheng, Lin Chen. 389-395 [doi]
• Relevance weighting of multi-term queries for Vector Space ModelLouis S. Wang. 396-402 [doi]
• An approximation algorithm for finding skeletal points for density based clustering approachesSoheil Hassas Yeganeh, Jafar Habibi, Hassan Abolhassani, Mahdi Abbaspour Tehrani, Jamshid Esmaelnezhad. 403-410 [doi]
• Mining Multiple Temporal Patterns of complex dynamic data systemsXin Feng, Odilon K. Senyana. 411-417 [doi]