Advances in Knowledge Discovery and Data Mining 14th Pacific-Asia Conference, PAKDD 2010, Hyderabad, India, June 21-24, 2010. Proceedings. Part I /
| Συγγραφή απο Οργανισμό/Αρχή: | |
|---|---|
| Άλλοι συγγραφείς: | , , , |
| Μορφή: | Ηλεκτρονική πηγή Ηλ. βιβλίο |
| Γλώσσα: | English |
| Έκδοση: |
Berlin, Heidelberg :
Springer Berlin Heidelberg,
2010.
|
| Σειρά: | Lecture Notes in Computer Science,
6118 |
| Θέματα: | |
| Διαθέσιμο Online: | Full Text via HEAL-Link |
Πίνακας περιεχομένων:
- 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.
