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

Detalles Bibliográficos
Clasificación:Libro Electrónico
Autor Corporativo: SpringerLink (Online service)
Otros Autores: Zaki, Mohammed J. (Editor ), Yu, Jeffrey Xu (Editor ), Ravindran, B. (Editor ), Pudi, Vikram (Editor )
Formato: Electrónico eBook
Idioma:Inglés
Publicado: Berlin, Heidelberg : Springer Berlin Heidelberg : Imprint: Springer, 2010.
Edición:1st ed. 2010.
Colección:Lecture Notes in Artificial Intelligence, 6118
Temas:
Acceso en línea:Texto Completo
Tabla de Contenidos:
  • Keynote Speeches
  • Empower People with Knowledge: The Next Frontier for Web Search
  • Discovery of Patterns in Global Earth Science Data Using Data Mining
  • Game Theoretic Approaches to Knowledge Discovery and Data Mining
  • Session 1A. Clustering I
  • A Set Correlation Model for Partitional Clustering
  • iVAT and aVAT: Enhanced Visual Analysis for Cluster Tendency Assessment
  • A Robust Seedless Algorithm for Correlation Clustering
  • Integrative Parameter-Free Clustering of Data with Mixed Type Attributes
  • Data Transformation for Sum Squared Residue
  • Session 1B. Social Networks
  • A Better Strategy of Discovering Link-Pattern Based Communities by Classical Clustering Methods
  • Mining Antagonistic Communities from Social Networks
  • As Time Goes by: Discovering Eras in Evolving Social Networks
  • Online Sampling of High Centrality Individuals in Social Networks
  • Estimate on Expectation for Influence Maximization in Social Networks
  • Session 1C. Classification I
  • A Novel Scalable Multi-class ROC for Effective Visualization and Computation
  • Efficiently Finding the Best Parameter for the Emerging Pattern-Based Classifier PCL
  • Rough Margin Based Core Vector Machine
  • BoostML: An Adaptive Metric Learning for Nearest Neighbor Classification
  • A New Emerging Pattern Mining Algorithm and Its Application in Supervised Classification
  • Session 2A. Privacy
  • Hiding Emerging Patterns with Local Recoding Generalization
  • Anonymizing Transaction Data by Integrating Suppression and Generalization
  • Satisfying Privacy Requirements: One Step before Anonymization
  • Computation of Ratios of Secure Summations in Multi-party Privacy-Preserving Latent Dirichlet Allocation
  • Privacy-Preserving Network Aggregation
  • Multivariate Equi-width Data Swapping for Private Data Publication
  • Session 2B. Spatio-Temporal Mining
  • Correspondence Clustering: An Approach to Cluster Multiple Related Spatial Datasets
  • Mining Trajectory Corridors Using Fréchet Distance and Meshing Grids
  • Subseries Join: A Similarity-Based Time Series Match Approach
  • TWave: High-Order Analysis of Spatiotemporal Data
  • Spatial Clustering with Obstacles Constraints by Dynamic Piecewise-Mapped and Nonlinear Inertia Weights PSO
  • Session 3A. Pattern Mining
  • An Efficient GA-Based Algorithm for Mining Negative Sequential Patterns
  • Valency Based Weighted Association Rule Mining
  • Ranking Sequential Patterns with Respect to Significance
  • Mining Association Rules in Long Sequences
  • Mining Closed Episodes from Event Sequences Efficiently
  • Most Significant Substring Mining Based on Chi-square Measure
  • Session 3B. Recommendations/Answers
  • Probabilistic User Modeling in the Presence of Drifting Concepts
  • Using Association Rules to Solve the Cold-Start Problem in Recommender Systems
  • Semi-supervised Tag Recommendation - Using Untagged Resources to Mitigate Cold-Start Problems
  • Cost-Sensitive Listwise Ranking Approach
  • Mining Wikipedia and Yahoo! Answers for Question Expansion in Opinion QA
  • Answer Diversification for Complex Question Answering on the Web
  • Vocabulary Filtering for Term Weighting in Archived Question Search
  • Session 3C. Topic Modeling/Information Extraction
  • On Finding the Natural Number of Topics with Latent Dirichlet Allocation: Some Observations
  • Supervising Latent Topic Model for Maximum-Margin Text Classification and Regression
  • Resource-Bounded Information Extraction: Acquiring Missing Feature Values on Demand
  • Efficient Deep Web Crawling Using Reinforcement Learning
  • Topic Decomposition and Summarization
  • Session 4A. Skylines/Uncertainty
  • UNN: A Neural Network for Uncertain Data Classification
  • SkyDist: Data Mining on Skyline Objects
  • Multi-Source Skyline Queries Processing in Multi-Dimensional Space
  • Efficient Pattern Mining of Uncertain Data with Sampling
  • Classifier Ensemble for Uncertain Data Stream Classification.