icdm 2010 论文列表
ICDM 2010, The 10th IEEE International Conference on Data Mining, Sydney, Australia, 14-17 December 2010.
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Discovering Multiple Clustering Solutions: Grouping Objects in Different Views of the Data.
How to Do Good Data Mining Research and Get it Published in Top Venues.
Knowledge Discovery in Academic Drug Discovery Programs: Opportunities and Challenges.
Spatial and Spatio-temporal Data Mining.
Efficient Episode Mining with Minimal and Non-overlapping Occurrences.
Frequent Instruction Sequential Pattern Mining in Hardware Sample Data.
Hierarchical Ensemble Clustering.
MoodCast: Emotion Prediction via Dynamic Continuous Factor Graph Model.
K-AP: Generating Specified K Clusters by Efficient Affinity Propagation.
Graph-Based Semi-supervised Learning with Adaptive Similarity Estimation.
Classifier and Cluster Ensembles for Mining Concept Drifting Data Streams.
ABS: The Anti Bouncing Model for Usage Data Streams.
Causal Discovery from Streaming Features.
Modeling Experts and Novices in Citizen Science Data for Species Distribution Modeling.
Passive Sampling for Regression.
Personalizing Web Page Recommendation via Collaborative Filtering and Topic-Aware Markov Model.
Max-Clique: A Top-Down Graph-Based Approach to Frequent Pattern Mining.
Collaborative Learning between Visual Content and Hidden Semantic for Image Retrieval.
Probabilistic Inference Protection on Anonymized Data.
What Do People Want in Microblogs? Measuring Interestingness of Hashtags in Twitter.
Homotopy Regularization for Boosting.
Anonymizing Temporal Data.
Compressed Nonnegative Sparse Coding.
Testing the Significance of Patterns in Data with Cluster Structure.
On the Vulnerability of Large Graphs.
Node Similarities from Spreading Activation.
Tru-Alarm: Trustworthiness Analysis of Sensor Networks in Cyber-Physical Systems.
Visualizing Graphs Using Minimum Spanning Dendrograms.
Averaged Stochastic Gradient Descent with Feedback: An Accurate, Robust, and Fast Training Method.
A System for Mining Temporal Physiological Data Streams for Advanced Prognostic Decision Support.
One-Class Matrix Completion with Low-Density Factorizations.
Transfer Learning on Heterogenous Feature Spaces via Spectral Transformation.
Efficient Semi-supervised Spectral Co-clustering with Constraints.
Interval-valued Matrix Factorization with Applications.
Topic Modeling Ensembles.
Generalized Probabilistic Matrix Factorizations for Collaborative Filtering.
Mixed-Membership Stochastic Block-Models for Transactional Networks.
Bonsai: Growing Interesting Small Trees.
An Approach for Automatic Sleep Stage Scoring and Apnea-Hypopnea Detection.
Accelerating Dynamic Time Warping Subsequence Search with GPUs and FPGAs.
Factorization Machines.
Leveraging D-Separation for Relational Data Sets.
Financial Forecasting with Gompertz Multiple Kernel Learning.
On Normalizing Fuzzy Coincidence Matrices to Compare Fuzzy and/or Possibilistic Partitions with the Rand Index.
Recommending Social Events from Mobile Phone Location Data.
A Generalized Linear Threshold Model for Multiple Cascades.
Assessing Data Mining Results on Matrices with Randomization.
Anomaly Detection Using an Ensemble of Feature Models.
Data Editing Techniques to Allow the Application of Distance-Based Outlier Detection to Streams.
On the Computation of Stochastic Search Variable Selection in Linear Regression with UDFs.
Sparse Boolean Matrix Factorizations.
Addressing Concept-Evolution in Concept-Drifting Data Streams.
Supervised Link Prediction Using Multiple Sources.
Transfer Learning via Cluster Correspondence Inference.
Understanding of Internal Clustering Validation Measures.
Efficient Probabilistic Latent Semantic Analysis with Sparsity Control.
Enforcing Vocabulary k-Anonymity by Semantic Similarity Based Clustering.
Micro-blogging Sentiment Detection by Collaborative Online Learning.
Mining Public Transport Usage for Personalised Intelligent Transport Systems.
Attribution of Conversion Events to Multi-channel Media.
Patterns on the Connected Components of Terabyte-Scale Graphs.
Discrimination Aware Decision Tree Learning.
Content-Based Methods for Predicting Web-Site Demographic Attributes.
Category Mining by Heterogeneous Data Fusion Using PdLSI Model in a Retail Service.
Multi-stream Join Answering for Mining Significant Cross-Stream Correlations.
Subspace Clustering Meets Dense Subgraph Mining: A Synthesis of Two Paradigms.
Minimizing the Variance of Cluster Mixture Models for Clustering Uncertain Objects.
Enhancing Single-Objective Projective Clustering Ensembles.
Accelerating Radius-Margin Parameter Selection for SVMs Using Geometric Bounds.
Advertising Campaigns Management: Should We Be Greedy?
Resilient K-d Trees: K-Means in Space Revisited.
The Effect of History on Modeling Systems' Performance: The Problem of the Demanding Lord.
Monotone Relabeling in Ordinal Classification.
Active Learning with Human-Like Noisy Oracle.
Block-GP: Scalable Gaussian Process Regression for Multimodal Data.
QMAS: Querying, Mining and Summarization of Multi-modal Databases.
Learning Preferences with Millions of Parameters by Enforcing Sparsity.
Location and Scatter Matching for Dataset Shift in Text Mining.
Pseudo Conditional Random Fields: Joint Training Approach to Segmenting and Labeling Sequence Data.
Active Improvement of Hierarchical Object Features under Budget Constraints.
On Finding Frequent Patterns in Event Sequences.
Approximation of Frequentness Probability of Itemsets in Uncertain Data.
Learning Collaborative Filtering and Its Application to People to People Recommendation in Social Networks.
Quantification via Probability Estimators.
Document Similarity Self-Join with MapReduce.
Two of a Kind or the Ratings Game? Adaptive Pairwise Preferences and Latent Factor Models.
SONNET: Efficient Approximate Nearest Neighbor Using Multi-core.
D-LDA: A Topic Modeling Approach without Constraint Generation for Semi-defined Classification.
Mother Fugger: Mining Historical Manuscripts with Local Color Patches.
Clustering Large Attributed Graphs: An Efficient Incremental Approach.
NESVM: A Fast Gradient Method for Support Vector Machines.
Improving Kernel Methods through Complex Data Mapping.
Network Simplification with Minimal Loss of Connectivity.
A Novel Contrast Co-learning Framework for Generating High Quality Training Data.
Active Learning from Multiple Noisy Labelers with Varied Costs.
Constraint Based Dimension Correlation and Distance Divergence for Clustering High-Dimensional Data.
Exploiting Unlabeled Data to Enhance Ensemble Diversity.
Term Filtering with Bounded Error.
Modeling Information Diffusion in Implicit Networks.
SMILE: A Similarity-Based Approach for Multiple Instance Learning.
Adaptive Distances on Sets of Vectors.
Discovering Overlapping Groups in Social Media.
Active Spectral Clustering.
Learning a Bi-Stochastic Data Similarity Matrix.
Weighted Feature Subset Non-negative Matrix Factorization and Its Applications to Document Understanding.
A Conscience On-line Learning Approach for Kernel-Based Clustering.
minCEntropy: A Novel Information Theoretic Approach for the Generation of Alternative Clusterings.
Multi-dimensional Mass Estimation and Mass-based Clustering.
Mining Closed Strict Episodes.
LogTree: A Framework for Generating System Events from Raw Textual Logs.
gSkeletonClu: Density-Based Network Clustering via Structure-Connected Tree Division or Agglomeration.
Discovering Correlated Subspace Clusters in 3D Continuous-Valued Data.
Polishing the Right Apple: Anytime Classification Also Benefits Data Streams with Constant Arrival Times.
Co-clustering of Lagged Data.
Decision Trees for Uplift Modeling.
Mining Sensor Streams for Discovering Human Activity Patterns over Time.
Consequences of Variability in Classifier Performance Estimates.
Separation of Interleaved Web Sessions with Heuristic Search.
Permutations as Angular Data: Efficient Inference in Factorial Spaces.
Bayesian Aggregation of Binary Classifiers.
A New SVM Approach to Multi-instance Multi-label Learning.
Edge Weight Regularization over Multiple Graphs for Similarity Learning.
A Log-Linear Model with Latent Features for Dyadic Prediction.
Multi-document Summarization Using Minimum Distortion.
Towards Structural Sparsity: An Explicit l2/l0 Approach.
Learning Markov Network Structure with Decision Trees.
Stratified Sampling for Data Mining on the Deep Web.
Training Conditional Random Fields Using Transfer Learning for Gesture Recognition.
Exploiting Local Data Uncertainty to Boost Global Outlier Detection.
Detecting Blackhole and Volcano Patterns in Directed Networks.
A Binary Decision Diagram-Based One-Class Classifier.
Multi-label Feature Selection for Graph Classification.
A Pairwise-Systematic Microaggregation for Statistical Disclosure Control.
An Approach Based on Tree Kernels for Opinion Mining of Online Product Reviews.
Improved Consistent Sampling, Weighted Minhash and L1 Sketching.
Algorithm for Discovering Low-Variance 3-Clusters from Real-Valued Datasets.
Rare Category Characterization.
Exponential Family Tensor Factorization for Missing-Values Prediction and Anomaly Detection.
A Variance Reduction Framework for Stable Feature Selection.
Efficient Discovery of the Top-K Optimal Dependency Rules with Fisher's Exact Test of Significance.
An Extensive Empirical Study on Semi-supervised Learning.
Learning Attribute-to-Feature Mappings for Cold-Start Recommendations.
Feature Selection for Unsupervised Learning Using Random Cluster Ensembles.
Subgroup Discovery Meets Bayesian Networks -- An Exceptional Model Mining Approach.
Sequential Latent Dirichlet Allocation: Discover Underlying Topic Structures within a Document.
PGLCM: Efficient Parallel Mining of Closed Frequent Gradual Itemsets.
Finding Local Anomalies in Very High Dimensional Space.
Viral Marketing for Multiple Products.
Bayesian Maximum Margin Clustering.
CLUSMASTER: A Clustering Approach for Sampling Data Streams in Sensor Networks.
Scalable Influence Maximization in Social Networks under the Linear Threshold Model.
A Graph-Based Approach for Multi-folder Email Classification.
Abstraction Augmented Markov Models.
iSAX 2.0: Indexing and Mining One Billion Time Series.
Fast and Flexible Multivariate Time Series Subsequence Search.
An Unsupervised Approach to Modeling Personalized Contexts of Mobile Users.
Spatiotemporal Event Detection in Mobility Network.
Multi-agent Random Walks for Local Clustering on Graphs.
Detecting Novel Discrepancies in Communication Networks.
10 Years of Data Mining Research: Retrospect and Prospect.
Assessing the Significance of Groups in High-Dimensional Data.
Mining Billion-node Graphs: Patterns, Generators and Tools.
