Dimensionality Reduction/Parallelism

• 
  Bin Tong, Einoshin Suzuki: Subclass-Oriented Dimension Reduction with Constraint Transformation and Manifold Regularization. 1-13
• 
  Panagis Magdalinos, Michalis Vazirgiannis, Dialecti Valsamou: Distributed Knowledge Discovery with Non Linear Dimensionality Reduction. 14-26
• 
  Jen-Wei Huang, Su-Chen Lin, Ming-Syan Chen: DPSP: Distributed Progressive Sequential Pattern Mining on the Cloud. 27-34
• 
  S. A. Arul Shalom, Manoranjan Dash, Minh Tue: An Approach for Fast Hierarchical Agglomerative Clustering Using Graphics Processors with CUDA. 35-42

Novel Applications

• 
  Haishan Liu, Gwen A. Frishkoff, Robert M. Frank, Dejing Dou: Ontology-Based Mining of Brainwaves: A Sequence Similarity Technique for Mapping Alternative Features in Event-Related Potentials (ERP) Data. 43-54
• 
  Tao Yang, Vojislav Kecman, Longbing Cao, Chengqi Zhang: Combining Support Vector Machines and the t-statistic for Gene Selection in DNA Microarray Data Analysis. 55-62
• 
  Hock Hee Ang, Vivekanand Gopalkrishnan, Anwitaman Datta, Wee Keong Ng, Steven C. H. Hoi: Satrap: Data and Network Heterogeneity Aware P2P Data-Mining. 63-70
• 
  Kyong Jin Shim, Richa Sharan, Jaideep Srivastava: Player Performance Prediction in Massively Multiplayer Online Role-Playing Games (MMORPGs). 71-80
• 
  Rajni Bala, R. K. Agrawal, Manju Sardana: Relevant Gene Selection Using Normalized Cut Clustering with Maximal Compression Similarity Measure. 81-88

Feature Selection/Visualization

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  Tao Yang, Longbing Cao, Chengqi Zhang: A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K >= 1. 89-100
• 
  Shiladitya Chowdhury, Jamuna Kanta Sing, Dipak Kumar Basu, Mita Nasipuri: Generalized Two-Dimensional FLD Method for Feature Extraction: An Application to Face Recognition. 101-112
• 
  Xinwei Jiang, Junbin Gao, Tianjiang Wang, Paul W. Kwan: Learning Gradients with Gaussian Processes. 113-124
• 
  Luigi Di Caro, Vanessa Frías-Martínez, Enrique Frías-Martínez: Analyzing the Role of Dimension Arrangement for Data Visualization in Radviz. 125-132

Graph Mining

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  Stephan Günnemann, Thomas Seidl: Subgraph Mining on Directed and Weighted Graphs. 133-146
• 
  Mutsumi Fukuzaki, Mio Seki, Hisashi Kashima, Jun Sese: Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph. 147-159
• 
  Sriganesh Srihari, Shruti Chandrashekar, Srinivasan Parthasarathy: A Framework for SQL-Based Mining of Large Graphs on Relational Databases. 160-167
• 
  Melissa Kasari, Hannu Toivonen, Petteri Hintsanen: Fast Discovery of Reliable k-terminal Subgraphs. 168-177
• 
  Akihiro Inokuchi, Takashi Washio: GTRACE2: Improving Performance Using Labeled Union Graphs. 178-188

Clustering II

• 
  Huifang Ma, Weizhong Zhao, Qing Tan, Zhongzhi Shi: Orthogonal Nonnegative Matrix Tri-factorization for Semi-supervised Document Co-clustering. 189-200
• 
  Dan He, Xindong Wu, Xingquan Zhu: Rule Synthesizing from Multiple Related Databases. 201-213
• 
  Zhao Li, Xindong Wu, Zhenyu Lu: Fast Orthogonal Nonnegative Matrix Tri-Factorization for Simultaneous Clustering. 214-221
• 
  Cindy Xide Lin, Yintao Yu, Jiawei Han, Bing Liu: Hierarchical Web-Page Clustering via In-Page and Cross-Page Link Structures. 222-229
• 
  Minoru Yoshida, Issei Sato, Hiroshi Nakagawa, Akira Terada: Mining Numbers in Text Using Suffix Arrays and Clustering Based on Dirichlet Process Mixture Models. 230-237

Opinion/Sentiment Mining

• 
  Muhammad Abulaish, Tanvir Ahmad, Jahiruddin, Mohammad Najmud Doja: Opinion-Based Imprecise Query Answering. 238-248
• 
  Peng Jiang, Chunxia Zhang, Qing Yang, Zhendong Niu: Blog Opinion Retrieval Based on Topic-Opinion Mixture Model. 249-260
• 
  Zhongwu Zhai, Hua Xu, Jun Li, Peifa Jia: Feature Subsumption for Sentiment Classification in Multiple Languages. 261-271
• 
  Yang Liao, Aaron Harwood, Kotagiri Ramamohanarao: Decentralisation of ScoreFinder: A Framework for Credibility Management on User-Generated Contents. 272-282
• 
  Thin Nguyen, Dinh Q. Phung, Brett Adams, Tran The Truyen, Svetha Venkatesh: Classification and Pattern Discovery of Mood in Weblogs. 283-290
• 
  Sukanya Manna, B. Sumudu U. Mendis, Tom Gedeon: Capture of Evidence for Summarization: An Application of Enhanced Subjective Logic. 291-298

Stream Mining

• 
  Albert Bifet, Geoffrey Holmes, Bernhard Pfahringer, Eibe Frank: Fast Perceptron Decision Tree Learning from Evolving Data Streams. 299-310
• 
  Mohammad M. Masud, Jing Gao, Latifur Khan, Jiawei Han, Bhavani M. Thuraisingham: Classification and Novel Class Detection in Data Streams with Active Mining. 311-324
• 
  Philipp Kranen, Ralph Krieger, Stefan Denker, Thomas Seidl: Bulk Loading Hierarchical Mixture Models for Efficient Stream Classification. 325-334
• 
  Yoann Pitarch, Anne Laurent, Pascal Poncelet: Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach. 335-342
• 
  Nesrine Gabsi, Fabrice Clérot, Georges Hébrail: Efficient Trade-Off between Speed Processing and Accuracy in Summarizing Data Streams. 343-353
• 
  Su-Chen Lin, Mi-Yen Yeh, Ming-Syan Chen: Subsequence Matching of Stream Synopses under the Time Warping Distance. 354-361

Similarity and Kernels

• 
  Julien Ah-Pine: Normalized Kernels as Similarity Indices. 362-373
• 
  Adam Woznica, Alexandros Kalousis, Melanie Hilario: Adaptive Matching Based Kernels for Labelled Graphs. 374-385
• 
  Adam Woznica, Alexandros Kalousis: A New Framework for Dissimilarity and Similarity Learning. 386-397
• 
  Weidong Yang, Hao Zhu: Semantic-Distance Based Clustering for XML Keyword Search. 398-409

Graph Analysis

• 
  Leman Akoglu, Mary McGlohon, Christos Faloutsos: oddball: Spotting Anomalies in Weighted Graphs. 410-421
• 
  Nguyen Lu Dang Khoa, Sanjay Chawla: Robust Outlier Detection Using Commute Time and Eigenspace Embedding. 422-434
• 
  B. Aditya Prakash, Ashwin Sridharan, Mukund Seshadri, Sridhar Machiraju, Christos Faloutsos: EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs. 435-448
• 
  Hanghang Tong, Spiros Papadimitriou, Christos Faloutsos, Philip S. Yu, Tina Eliassi-Rad: BASSET: Scalable Gateway Finder in Large Graphs. 449-463

Classification II

• 
  Qing Wang, Liang Zhang: Ensemble Learning Based on Multi-Task Class Labels. 464-475
• 
  Eileen A. Ni, Charles X. Ling: Supervised Learning with Minimal Effort. 476-487
• 
  T. Ryan Hoens, Nitesh V. Chawla: Generating Diverse Ensembles to Counter the Problem of Class Imbalance. 488-499
• 
  Kuo-Wei Hsu, Jaideep Srivastava: Relationship between Diversity and Correlation in Multi-Classifier Systems. 500-506
• 
  Bo Dai, Gang Niu: Compact Margin Machine. 507-514

last updated on Tue May 21 02:22:48 2013 by the dblp team
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