icdm 2011 论文列表
11th IEEE International Conference on Data Mining, ICDM 2011, Vancouver, BC, Canada, December 11-14, 2011.
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Text Clustering via Constrained Nonnegative Matrix Factorization.
A Study of Laplacian Spectra of Graph for Subgraph Queries.
Low Rank Metric Learning with Manifold Regularization.
Discovering Thematic Patterns in Videos via Cohesive Sub-graph Mining.
Tensor Fold-in Algorithms for Social Tagging Prediction.
Classifying Categorical Data by Rule-Based Neighbors.
Review Graph Based Online Store Review Spammer Detection.
Finding Communities in Dynamic Social Networks.
Discovering Emerging Topics in Social Streams via Link Anomaly Detection.
Identities Anonymization in Dynamic Social Networks.
A New Multi-task Learning Method for Personalized Activity Recognition.
A Fast and Flexible Clustering Algorithm Using Binary Discretization.
Clustering with Attribute-Level Constraints.
Distance Preserving Graph Simplification.
Helix: Unsupervised Grammar Induction for Structured Activity Recognition.
Cross-Temporal Link Prediction.
Performances and Characteristics of DIGRank, Ranking in the Incomplete Networks.
Detecting Recurring and Novel Classes in Concept-Drifting Data Streams.
Optimizing Performance Measures for Feature Selection.
Mixture of Softmax sLDA.
Web Horror Image Recognition Based on Context-Aware Multi-instance Learning.
Scalable Diversified Ranking on Large Graphs.
Calculating Feature Weights in Naive Bayes with Kullback-Leibler Measure.
Co-clustering for Binary and Categorical Data with Maximum Modularity.
Modeling High-Level Behavior Patterns for Precise Similarity Analysis of Software.
Using Frequent Closed Itemsets for Data Dimensionality Reduction.
Semi-supervised Discriminant Hashing.
Entropy-Based Graph Clustering: Application to Biological and Social Networks.
Learning from Negative Examples in Set-Expansion.
ASAP: A Self-Adaptive Prediction System for Instant Cloud Resource Demand Provisioning.
A Fixed Parameter Tractable Integer Program for Finding the Maximum Order Preserving Submatrix.
Discovery of Versatile Temporal Subspace Patterns in 3-D Datasets.
Discovering the Intrinsic Cardinality and Dimensionality of Time Series Using MDL.
Constraint Selection-Based Semi-supervised Feature Selection.
Twin Gaussian Processes for Binary Classification.
How Does Research Evolve? Pattern Mining for Research Meme Cycles.
Learning Protein Folding Energy Functions.
Tracking and Connecting Topics via Incremental Hierarchical Dirichlet Processes.
A Spectral Framework for Detecting Inconsistency across Multi-source Object Relationships.
Efficient Mining of Closed Sequential Patterns on Stream Sliding Window.
Identifying Differentially Expressed Genes via Weighted Rank Aggregation.
Unsupervised Anomaly Intrusion Detection via Localized Bayesian Feature Selection.
Supervised Lazy Random Walk for Topic-Focused Multi-document Summarization.
Characterizing Inverse Time Dependency in Multi-class Learning.
Manifold Learning and Missing Data Recovery through Unsupervised Regression.
SPO: Structure Preserving Oversampling for Imbalanced Time Series Classification.
On the Hardness of Graph Anonymization.
Handling Conditional Discrimination.
Semi-supervised Hierarchical Clustering.
Finding Novel Diagnostic Gene Patterns Based on Interesting Non-redundant Contrast Sequence Rules.
Positive and Unlabeled Learning for Graph Classification.
Fast and Robust Graph-based Transductive Learning via Minimum Tree Cut.
Clusterability Analysis and Incremental Sampling for Nyström Extension Based Spectral Clustering.
Enabling Fast Lazy Learning for Data Streams.
Multi-task Learning for Bayesian Matrix Factorization.
Causal Associative Classification.
LPTA: A Probabilistic Model for Latent Periodic Topic Analysis.
Secure Clustering in Private Networks.
Multi-task Learning with Task Relations.
Multi-instance Metric Learning.
BibClus: A Clustering Algorithm of Bibliographic Networks by Message Passing on Center Linkage Structure.
A New Markov Model for Clustering Categorical Sequences.
Direct Robust Matrix Factorizatoin for Anomaly Detection.
Understanding Propagation Error and Its Effect on Collective Classification.
Efficient Mining of a Concise and Lossless Representation of High Utility Itemsets.
Using Bayesian Network Learning Algorithm to Discover Causal Relations in Multivariate Time Series.
Document Clustering via Matrix Representation.
ADANA: Active Name Disambiguation.
Detecting Community Kernels in Large Social Networks.
Nonnegative Matrix Tri-factorization Based High-Order Co-clustering and Its Fast Implementation.
Combining Feature Context and Spatial Context for Image Pattern Discovery.
Class Imbalance, Redux.
Random Forest Based Feature Induction.
Conditional Anomaly Detection with Soft Harmonic Functions.
Diverse Dimension Decomposition of an Itemset Space.
Density Estimation Based on Mass.
Finding Robust Itemsets under Subsampling.
Recursive Multi-step Time Series Forecasting by Perturbing Data.
On Generating All Optimal Monotone Classifications.
Interesting Multi-relational Patterns.
Ranking Web-Based Partial Orders by Significance Using a Markov Reference Model.
Mining Dominant Patterns in the Sky.
Partitionable Kernels for Mapping Kernels.
Simple Multiple Noisy Label Utilization Strategies.
Learning to Rank for Query-Focused Multi-document Summarization.
A Generalized Fast Subset Sums Framework for Bayesian Event Detection.
Detection of Arbitrarily Oriented Synchronized Clusters in High-Dimensional Data.
Learning Spectral Embedding for Semi-supervised Clustering.
An In-depth Study of Stochastic Kronecker Graphs.
Healing Sample Selection Bias by Source Classifier Selection.
Analysis of Textual Variation by Latent Tree Structures.
Mining Historical Documents for Near-Duplicate Figures.
Time Series Epenthesis: Clustering Time Series Streams Requires Ignoring Some Data.
Threshold Conditions for Arbitrary Cascade Models on Arbitrary Networks.
Detection of Cross-Channel Anomalies from Multiple Data Channels.
An Analysis of Performance Measures for Binary Classifiers.
Novel Recommendation Based on Personal Popularity Tendency.
SLIM: Sparse Linear Methods for Top-N Recommender Systems.
Word Cloud Model for Text Categorization.
Learning Classification with Auxiliary Probabilistic Information.
Incremental Elliptical Boundary Estimation for Anomaly Detection in Wireless Sensor Networks.
Sparse Domain Adaptation in Projection Spaces Based on Good Similarity Functions.
Boolean Tensor Factorizations.
Privacy Risk in Graph Stream Publishing for Social Network Data.
Minimizing Seed Set for Viral Marketing.
Tag Clustering and Refinement on Semantic Unity Graph.
Personalized Travel Package Recommendation.
A Hypergraph-based Method for Discovering Semantically Associated Itemsets.
Towards Optimal Discriminating Order for Multiclass Classification.
The Joint Inference of Topic Diffusion and Evolution in Social Communities.
Context-Aware Multi-instance Learning Based on Hierarchical Sparse Representation.
Local Models for Expectation-Driven Subgroup Discovery.
Maximum Entropy Modelling for Assessing Results on Real-Valued Data.
TWITOBI: A Recommendation System for Twitter Using Probabilistic Modeling.
Signature Pattern Covering via Local Greedy Algorithm and Pattern Shrink.
Learning Markov Logic Networks via Functional Gradient Boosting.
Improving Product Classification Using Images.
Beyond 'Caveman Communities': Hubs and Spokes for Graph Compression and Mining.
S-preconditioner for Multi-fold Data Reduction with Guaranteed User-Controlled Accuracy.
Patent Maintenance Recommendation with Patent Information Network Model.
A Robust Clustering Algorithm Based on Aggregated Heat Kernel Mapping.
Generating Breakpoint-based Timeline Overview for News Topic Retrospection.
Learning Tags from Unsegmented Videos of Multiple Human Actions.
Heuristic Updatable Weighted Random Subspaces for Non-stationary Environments.
Flexible Fault Tolerant Subspace Clustering for Data with Missing Values.
Cross Domain Random Walk for Query Intent Pattern Mining from Search Engine Log.
SIMPATH: An Efficient Algorithm for Influence Maximization under the Linear Threshold Model.
D-cores: Measuring Collaboration of Directed Graphs Based on Degeneracy.
Isograph: Neighbourhood Graph Construction Based on Geodesic Distance for Semi-supervised Learning.
A Taxi Driving Fraud Detection System.
Structured Feature Selection and Task Relationship Inference for Multi-task Learning.
An Efficient Greedy Method for Unsupervised Feature Selection.
Exploiting False Discoveries - Statistical Validation of Patterns and Quality Measures in Subgroup Discovery.
Learning Dirichlet Processes from Partially Observed Groups.
LinkBoost: A Novel Cost-Sensitive Boosting Framework for Community-Level Network Link Prediction.
CEMiner - An Efficient Algorithm for Mining Closed Patterns from Time Interval-Based Data.
Efficiently Mining Unordered Trees.
SolarMap: Multifaceted Visual Analytics for Topic Exploration.
Multi-Class L2, 1-Norm Support Vector Machine.
Mining Heavy Subgraphs in Time-Evolving Networks.
Confidence in Predictions from Random Tree Ensembles.
Learning with Minimum Supervision: A General Framework for Transductive Transfer Learning.
Overlapping Correlation Clustering.
COMET: A Recipe for Learning and Using Large Ensembles on Massive Data.
Semi-supervised Feature Importance Evaluation with Ensemble Learning.
Role-Behavior Analysis from Trajectory Data by Cross-Domain Learning.
Infrastructure Pattern Discovery in Configuration Management Databases via Large Sparse Graph Mining.
Algorithms for Mining the Evolution of Conserved Relational States in Dynamic Networks.
