icdm 2009 论文列表ICDM 2009, The Ninth IEEE International Conference on Data Mining, Miami, Florida, USA, 6-9 December 2009. |
A New Kernel-Based Classification Algorithm.
A Cost-Effective LSH Filter for Fast Pairwise Mining.
RING: An Integrated Method for Frequent Representative Subgraph Mining.
Learning Local Components to Understand Large Bayesian Networks.
Multirelational Topic Models.
Non-sparse Multiple Kernel Learning for Fisher Discriminant Analysis.
A New MCA-Based Divisive Hierarchical Algorithm for Clustering Categorical Data.
Bi-relational Network Analysis Using a Fast Random Walk with Restart.
Binomial Matrix Factorization for Discrete Collaborative Filtering.
Effective Criterion Functions for Efficient Agglomerative Clustering on Very Large Networks.
Discovering Contexts and Contextual Outliers Using Random Walks in Graphs.
Maximum Margin Clustering on Data Manifolds.
Two Heads Better Than One: Metric+Active Learning and its Applications for IT Service Classification.
Clustering with Multiple Graphs.
Topic Distributions over Links on Web.
Feature Selection in the Tensor Product Feature Space.
Spatio-temporal Energy Based Gait Recognition.
A Global-Model Naive Bayes Approach to the Hierarchical Prediction of Protein Functions.
Combining Super-Structuring and Abstraction on Sequence Classification.
Topic Modeling for Sequences of Temporal Activities.
Hierarchical Probabilistic Segmentation of Discrete Events.
A Fully Automated Method for Discovering Community Structures in High Dimensional Data.
Aspect Guided Text Categorization with Unobserved Labels.
Global Slope Change Synopses for Measurement Maps.
Constraint-Based Pattern Mining in Dynamic Graphs.
Naive Bayes Classification of Uncertain Data.
Kernel Conditional Quantile Estimation via Reduction Revisited.
Discovering Organizational Structure in Dynamic Social Network.
Online and Batch Learning of Generalized Cosine Similarities.
PUB: A Class Description Technique Based on Partial Coverage of Subspace.
Interaction-Based Clustering of Multivariate Time Series.
Permutation Tests for Studying Classifier Performance.
Analysis of Subsequence Time-Series Clustering Based on Moving Average.
To Trust or Not to Trust? Predicting Online Trusts Using Trust Antecedent Framework.
Automatically Extracting Dialog Models from Conversation Transcripts.
A New Clustering Algorithm Based on Regions of Influence with Self-Detection of the Best Number of Clusters.
Promoting Total Efficiency in Text Clustering via Iterative and Interactive Metric Learning.
On the (In)Security and (Im)Practicality of Outsourcing Precise Association Rule Mining.
Multi-document Summarization by Information Distance.
A Contrast Pattern Based Clustering Quality Index for Categorical Data.
Sparse Norm-Regularized Reconstructive Coefficients Learning.
VIF Regression: A Fast Regression Algorithm for Large Data.
Semi-supervised Density-Based Clustering.
A Walk from 2-Norm SVM to 1-Norm SVM.
Redistricting Using Heuristic-Based Polygonal Clustering.
Modeling Syntactic Structures of Topics with a Nested HMM-LDA.
A Bootstrap Approach to Eigenvalue Correction.
Parallel PathFinder Algorithms for Mining Structures from Graphs.
An Effective Approach to Inverse Frequent Set Mining.
Knowledge Discovery from Citation Networks.
Projective Clustering Ensembles.
Regression Learning Vector Quantization.
Unsupervised Relation Extraction by Massive Clustering.
Bayesian Overlapping Subspace Clustering.
Finding Maximal Fully-Correlated Itemsets in Large Databases.
Large Scale Relation Acquisition Using Class Dependent Patterns.
Active Selection of Sensor Sites in Remote Sensing Applications.
CoFKM: A Centralized Method for Multiple-View Clustering.
Accelerated Gradient Method for Multi-task Sparse Learning Problem.
Fine-Grain Perturbation for Privacy Preserving Data Publishing.
Efficient Algorithm for Computing Link-Based Similarity in Real World Networks.
Hierarchical Bayesian Models for Collaborative Tagging Systems.
Effective Anomaly Detection in Sensor Networks Data Streams.
SLIDER: Mining Correlated Motifs in Protein-Protein Interaction Networks.
Dirichlet Mixture Allocation for Multiclass Document Collections Modeling.
Algorithms for Large, Sparse Network Alignment Problems.
Joint Emotion-Topic Modeling for Social Affective Text Mining.
Outlier Detection Using Inductive Logic Programming.
An L-infinity Norm Visual Classifier.
P-packSVM: Parallel Primal grAdient desCent Kernel SVM.
Inverse Time Dependency in Convex Regularized Learning.
Vague One-Class Learning for Data Streams.
Efficient Discovery of Confounders in Large Data Sets.
Maximum Margin Clustering with Multivariate Loss Function.
Mining Data Streams with Labeled and Unlabeled Training Examples.
Filtering and Refinement: A Two-Stage Approach for Efficient and Effective Anomaly Detection.
Peculiarity Analysis for Classifications.
Synthesizing Novel Dimension Reduction Algorithms in Matrix Trace Oriented Optimization Framework.
Online System Problem Detection by Mining Patterns of Console Logs.
Mining Peculiarity Groups in Day-by-Day Behavioral Datasets.
Fast Online Training of Ramp Loss Support Vector Machines.
Semi-supervised Multi-task Learning with Task Regularizations.
Extracting Output Metadata from Scientific Deep Web Data Sources.
Scalable Classification in Large Scale Spatiotemporal Domains Applied to Voltage-Sensitive Dye Imaging.
On K-Means Cluster Preservation Using Quantization Schemes.
Convex Non-negative Matrix Factorization in the Wild.
Significance of Episodes Based on Minimal Windows.
Uncoverning Groups via Heterogeneous Interaction Analysis.
iTopicModel: Information Network-Integrated Topic Modeling.
Extending Semi-supervised Learning Methods for Inductive Transfer Learning.
Argumentation Based Constraint Acquisition.
Discriminative Mixed-Membership Models.
Resolving Identity Uncertainty with Learned Random Walks.
A Sparsification Approach for Temporal Graphical Model Decomposition.
Semi-Markov kMeans Clustering and Activity Recognition from Body-Worn Sensors.
Semi-Supervised Sequence Labeling with Self-Learned Features.
Clustering Trajectories of Moving Objects in an Uncertain World.
Discovering Excitatory Networks from Discrete Event Streams with Applications to Neuronal Spike Train Analysis.
Evaluating Statistical Tests for Within-Network Classifiers of Relational Data.
Stacked Gaussian Process Learning.
Relevant Subspace Clustering: Mining the Most Interesting Non-redundant Concepts in High Dimensional Data.
Finding Time Series Motifs in Disk-Resident Data.
A Deep Non-linear Feature Mapping for Large-Margin kNN Classification.
Scalable Algorithms for Distribution Search.
Non-negative Laplacian Embedding.
Active Learning with Adaptive Heterogeneous Ensembles.
Extended Boolean Matrix Decomposition.
Unified Solution to Nonnegative Data Factorization Problems.
Least Square Incremental Linear Discriminant Analysis.
A Framework for Computing the Privacy Scores of Users in Online Social Networks.
Semi-naive Exploitation of One-Dependence Estimators.
CoCoST: A Computational Cost Efficient Classifier.
Improving SVM Classification on Imbalanced Data Sets in Distance Spaces.
Self-Adaptive Anytime Stream Clustering.
Efficient Discovery of Frequent Correlated Subgraph Pairs.
PEGASUS: A Peta-Scale Graph Mining System.
TrBagg: A Simple Transfer Learning Method and its Application to Personalization in Collaborative Tagging.
A Tree-Based Framework for Difference Summarization.
GRAPE: A Graph-Based Framework for Disambiguating People Appearances in Web Search.
GSML: A Unified Framework for Sparse Metric Learning.
A Linear-Time Graph Kernel.
Accurate Estimation of the Degree Distribution of Private Networks.
Learning the Shared Subspace for Multi-task Clustering and Transductive Transfer Classification.
Execution Anomaly Detection in Distributed Systems through Unstructured Log Analysis.
Unsupervised Class Separation of Multivariate Data through Cumulative Variance-Based Ranking.
Conditional Models for Non-smooth Ranking Loss Functions.
Active Learning with Generalized Queries.
Temporal Neighborhood Discovery Using Markov Models.
?-Anomica: A Fast Support Vector Based Novelty Detection Technique.
flowNet: Flow-Based Approach for Efficient Analysis of Complex Biological Networks.
Probabilistic Similarity Query on Dimension Incomplete Data.
Beyond Banditron: A Conservative and Efficient Reduction for Online Multiclass Prediction with Bandit Setting Model.
Finding Associations and Computing Similarity via Biased Pair Sampling.
Audio Classification of Bird Species: A Statistical Manifold Approach.
Cross-Guided Clustering: Transfer of Relevant Supervision across Domains for Improved Clustering.
A Local Scalable Distributed Expectation Maximization Algorithm for Large Peer-to-Peer Networks.
Rule Ensembles for Multi-target Regression.
Connecting Sparsely Distributed Similar Bloggers.
Explore/Exploit Schemes for Web Content Optimization.