Advances in Knowledge Discovery and Data Mining 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part II /

• Corporate Author: SpringerLink (Online service)
• Other Authors: Zaki, Mohammed J. (Editor), Yu, Jeffrey Xu (Editor), Ravindran, B. (Editor), Pudi, Vikram (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2010.
• Series: Lecture Notes in Computer Science, 6119
• Subjects: Computer science.; Algorithms.; Database management.; Data mining.; Information storage and retrieval.; Artificial intelligence.; Computer Science.; Data Mining and Knowledge Discovery.; Artificial Intelligence (incl. Robotics).; Information Systems Applications (incl. Internet).; Information Storage and Retrieval.; Database Management.; Algorithm Analysis and Problem Complexity.

 Session 4B. Dimensionality Reduction/Parallelism -- Subclass-Oriented Dimension Reduction with Constraint Transformation and Manifold Regularization -- Distributed Knowledge Discovery with Non Linear Dimensionality Reduction -- DPSP: Distributed Progressive Sequential Pattern Mining on the Cloud -- An Approach for Fast Hierarchical Agglomerative Clustering Using Graphics Processors with CUDA -- Session 5A. Novel Applications -- Ontology-Based Mining of Brainwaves: A Sequence Similarity Technique for Mapping Alternative Features in Event-Related Potentials (ERP) Data -- Combining Support Vector Machines and the t-statistic for Gene Selection in DNA Microarray Data Analysis -- Satrap: Data and Network Heterogeneity Aware P2P Data-Mining -- Player Performance Prediction in Massively Multiplayer Online Role-Playing Games (MMORPGs) -- Relevant Gene Selection Using Normalized Cut Clustering with Maximal Compression Similarity Measure -- Session 5B. Feature Selection/Visualization -- A Novel Prototype Reduction Method for the K-Nearest Neighbor Algorithm with K???1 -- Generalized Two-Dimensional FLD Method for Feature Extraction: An Application to Face Recognition -- Learning Gradients with Gaussian Processes -- Analyzing the Role of Dimension Arrangement for Data Visualization in Radviz -- Session 6A. Graph Mining -- Subgraph Mining on Directed and Weighted Graphs -- Finding Itemset-Sharing Patterns in a Large Itemset-Associated Graph -- A Framework for SQL-Based Mining of Large Graphs on Relational Databases -- Fast Discovery of Reliable k-terminal Subgraphs -- GTRACE2: Improving Performance Using Labeled Union Graphs -- Session 6B. Clustering II -- Orthogonal Nonnegative Matrix Tri-factorization for Semi-supervised Document Co-clustering -- Rule Synthesizing from Multiple Related Databases -- Fast Orthogonal Nonnegative Matrix Tri-Factorization for Simultaneous Clustering -- Hierarchical Web-Page Clustering via In-Page and Cross-Page Link Structures -- Mining Numbers in Text Using Suffix Arrays and Clustering Based on Dirichlet Process Mixture Models -- Session 7A. Opinion/Sentiment Mining -- Opinion-Based Imprecise Query Answering -- Blog Opinion Retrieval Based on Topic-Opinion Mixture Model -- Feature Subsumption for Sentiment Classification in Multiple Languages -- Decentralisation of ScoreFinder: A Framework for Credibility Management on User-Generated Contents -- Classification and Pattern Discovery of Mood in Weblogs -- Capture of Evidence for Summarization: An Application of Enhanced Subjective Logic -- Session 7B. Stream Mining -- Fast Perceptron Decision Tree Learning from Evolving Data Streams -- Classification and Novel Class Detection in Data Streams with Active Mining -- Bulk Loading Hierarchical Mixture Models for Efficient Stream Classification -- Summarizing Multidimensional Data Streams: A Hierarchy-Graph-Based Approach -- Efficient Trade-Off between Speed Processing and Accuracy in Summarizing Data Streams -- Subsequence Matching of Stream Synopses under the Time Warping Distance -- Session 8A. Similarity and Kernels -- Normalized Kernels as Similarity Indices -- Adaptive Matching Based Kernels for Labelled Graphs -- A New Framework for Dissimilarity and Similarity Learning -- Semantic-Distance Based Clustering for XML Keyword Search -- Session 8B. Graph Analysis -- oddball: Spotting Anomalies in Weighted Graphs -- Robust Outlier Detection Using Commute Time and Eigenspace Embedding -- EigenSpokes: Surprising Patterns and Scalable Community Chipping in Large Graphs -- BASSET: Scalable Gateway Finder in Large Graphs -- Session 8C. Classification II -- Ensemble Learning Based on Multi-Task Class Labels -- Supervised Learning with Minimal Effort -- Generating Diverse Ensembles to Counter the Problem of Class Imbalance -- Relationship between Diversity and Correlation in Multi-Classifier Systems -- Compact Margin Machine.