icdm 2015 论文列表2015 IEEE International Conference on Data Mining, ICDM 2015, Atlantic City, NJ, USA, November 14-17, 2015. |
Representation Learning via Semi-Supervised Autoencoder for Multi-task Learning.
Rare Category Detection on Time-Evolving Graphs.
Domain Induced Dirichlet Mixture of Gaussian Processes: An Application to Predicting Disease Progression in Multiple Sclerosis Patients.
Part-Level Regularized Semi-Nonnegative Coding for Semi-Supervised Learning.
A Cure Time Model for Joint Prediction of Outcome and Time-to-Outcome.
Towards Mining Trapezoidal Data Streams.
MMFE: Multitask Multiview Feature Embedding.
Collaborated Online Change-Point Detection in Sparse Time Series for Online Advertising.
A Multi-label Ensemble Method Based on Minimum Ranking Margin Maximization.
Freedom: Online Activity Recognition via Dictionary-Based Sparse Representation of RFID Sensing Data.
A Graph-Based Hybrid Framework for Modeling Complex Heterogeneity.
Semantic-Based Recommendation Across Heterogeneous Domains.
Forensic Style Analysis with Survival Trajectories.
Pranjul Yadav Michael S. Steinbach Lisiane Pruinelli Bonnie L. Westra Connie Delaney Vipin Kumar György J. Simon
Feature Selection with Integrated Relevance and Redundancy Optimization.
Learning Career Mobility and Human Activity Patterns for Job Change Analysis.
Towards Collusive Fraud Detection in Online Reviews.
A Data Driven Approach to Uncover Deficiencies in Online Reputation Systems.
Spammers Detection from Product Reviews: A Hybrid Model.
Sequential Model-Free Hyperparameter Tuning.
GS-Orthogonalization Based "Basis Feature" Selection from Word Co-occurrence Matrix.
A Hierarchical Pattern Learning Framework for Forecasting Extreme Weather Events.
KnowSim: A Document Similarity Measure on Structured Heterogeneous Information Networks.
Efficient Approximate Solutions to Mutual Information Based Global Feature Selection.
Having a Blast: Meta-Learning and Heterogeneous Ensembles for Data Streams.
A Generative Spatial Clustering Model for Random Data through Spanning Trees.
Hierarchies in Directed Networks.
Geo-Social Clustering of Places from Check-in Data.
Catching the Head, Tail, and Everything in Between: A Streaming Algorithm for the Degree Distribution.
From 0.5 Million to 2.5 Million: Efficiently Scaling up Real-Time Bidding.
Nonparametric Poisson Factorization Machine.
Finding Time-Critical Responses for Information Seeking in Social Media.
Differentially Private Random Forest with High Utility.
Task Assignment Optimization in Collaborative Crowdsourcing.
Sparse Hierarchical Tucker Factorization and Its Application to Healthcare.
Quality Control for Crowdsourced Hierarchical Classification.
Two-Step Heterogeneous Finite Mixture Model Clustering for Mining Healthcare Databases.
Experience-Aware Item Recommendation in Evolving Review Communities.
Outcomes Prediction via Time Intervals Related Patterns.
CrowdTC: Crowdsourced Taxonomy Construction.
Personalized Grade Prediction: A Data Mining Approach.
Absorbing Random-Walk Centrality: Theory and Algorithms.
Missing Value Estimation for Hierarchical Time Series: A Study of Hierarchical Web Traffic.
Spatio-Temporal Topic Models for Check-in Data.
Station Site Optimization in Bike Sharing Systems.
Clustering with Partition Level Side Information.
Logdet Divergence Based Sparse Non-Negative Matrix Factorization for Stable Representation.
Learning User Preferences across Multiple Aspects for Merchant Recommendation.
DRN: Bringing Greedy Layer-Wise Training into Time Dimension.
The Convergence Behavior of Naive Bayes on Large Sparse Datasets.
Analysis of Spectral Space Properties of Directed Graphs Using Matrix Perturbation Theory with Application in Graph Partition.
Iterative Classification for Sanitizing Large-Scale Datasets.
Fast Matrix-Vector Multiplications for Large-Scale Logistic Regression on Shared-Memory Systems.
Measuring Large-Scale Dynamic Graph Similarity by RICom: RWR with Intergraph Compression.
LambdaMF: Learning Nonsmooth Ranking Functions in Matrix Factorization Using Lambda.
Theoretical and Empirical Criteria for the Edited Nearest Neighbour Classifier.
Transfer Learning via Relational Type Matching.
Variable Selection for Efficient Nonnegative Tensor Factorization.
Post Classification Label Refinement Using Implicit Ordering Constraint Among Data Instances.
Supervised Topic Models for Microblog Classification.
Adaptive Heterogeneous Ensemble Learning Using the Context of Test Instances.
A General Suspiciousness Metric for Dense Blocks in Multimodal Data.
Scalable Hypergraph Learning and Processing.
Detecting Overlapping Communities from Local Spectral Subspaces.
Population Synthesis via k-Nearest Neighbor Crossover Kernel.
CNL: Collective Network Linkage Across Heterogeneous Social Platforms.
Patent Citation Recommendation for Examiners.
A Parameter-Free Approach for Mining Robust Sequential Classification Rules.
Dissecting Regional Weather-Traffic Sensitivity Throughout a City.
The ABACOC Algorithm: A Novel Approach for Nonparametric Classification of Data Streams.
Efficient Entity Resolution with Adaptive and Interactive Training Data Selection.
Constructing Disease Network and Temporal Progression Model via Context-Sensitive Hawkes Process.
On the Connectivity of Multi-layered Networks: Models, Measures and Optimal Control.
Mining Brain Networks Using Multiple Side Views for Neurological Disorder Identification.
Automated Feature Learning: Mining Unstructured Data for Useful Abstractions.
Are You Going to the Party: Depends, Who Else is Coming?: [Learning Hidden Group Dynamics via Conditional Latent Tree Models].
Learning Set Cardinality in Distance Nearest Neighbours.
Learning a Macroscopic Model of Cultural Dynamics.
Simultaneous Semi-NMF and PCA for Clustering.
Complementary Aspect-Based Opinion Mining Across Asymmetric Collections.
Top-k Reliability Search on Uncertain Graphs.
Cost-Sensitive Online Classification with Adaptive Regularization and Its Applications.
SimNest: Social Media Nested Epidemic Simulation via Online Semi-Supervised Deep Learning.
Parallel Multi-task Learning.
Controlling Propagation at Group Scale on Networks.
Modeling Social Attention for Stock Analysis: An Influence Propagation Perspective.
Multiple Anonymized Social Networks Alignment.
A Bayesian Hierarchical Model for Comparing Average F1 Scores.
Deep Convolutional Neural Networks for Multi-instance Multi-task Learning.
Max-Intensity: Detecting Competitive Advertiser Communities in Sponsored Search Market.
From Micro to Macro: Uncovering and Predicting Information Cascading Process with Behavioral Dynamics.
Weighted Spectral Cluster Ensemble.
Fast Low-Rank Matrix Learning with Nonconvex Regularization.
Sparse Online Relative Similarity Learning.
Beyond Query: Interactive User Intention Understanding.
An Aggressive Graph-Based Selective Sampling Algorithm for Classification.
Exploiting Temporal and Social Factors for B2B Marketing Campaign Recommendations.
Infinite Author Topic Model Based on Mixed Gamma-Negative Binomial Process.
Convex Approximation to the Integral Mixture Models Using Step Functions.
R2FP: Rich and Robust Feature Pooling for Mining Visual Data.
Collaborative Multi-domain Sentiment Classification.
KSTR: Keyword-Aware Skyline Travel Route Recommendation.
Multi-level Approximate Spectral Clustering.
Mining Multi-aspect Reflection of News Events in Twitter: Discovery, Linking and Presentation.
Experimental Design with Multiple Kernels.
Modeling Adoption and Usage of Competing Products.
The Impact of Patent Activities on Stock Dynamics in the High-Tech Sector.
Top-k Link Recommendation in Social Networks.
BrainQuest: Perception-Guided Brain Network Comparison.
Online Model Evaluation in a Large-Scale Computational Advertising Platform.
Fast Parallel Mining of Maximally Informative k-Itemsets in Big Data.
Domain-Specific Knowledge Base Enrichment Using Wikipedia Tables.
Predicting Sports Scoring Dynamics with Restoration and Anti-Persistence.
Ensemble Kernel Mean Matching.
Accelerating Exact Similarity Search on CPU-GPU Systems.
Parallel Hierarchical Clustering in Linearithmic Time for Large-Scale Sequence Analysis.
A Unified Gradient Regularization Family for Adversarial Examples.
Robust Multi-Network Clustering via Joint Cross-Domain Cluster Alignment.
Mining Indecisiveness in Customer Behaviors.
Community Detection Based on Structure and Content: A Content Propagation Perspective.
Content-Aware Collaborative Filtering for Location Recommendation Based on Human Mobility Data.
Leveraging Implicit Relative Labeling-Importance Information for Effective Multi-label Learning.
Generative Models for Mining Latent Aspects and Their Ratings from Short Reviews.
Point-of-Interest Recommender Systems: A Separate-Space Perspective.
Automatic Taxonomy Extraction from Bipartite Graphs.
Robust PCA Via Nonconvex Rank Approximation.
Traveling Salesman in Reverse: Conditional Markov Entropy for Trajectory Segmentation.
Informative Prediction Based on Ordinal Questionnaire Data.
Learning Label Specific Features for Multi-label Classification.
Finding Multiple Stable Clusterings.
Time Series Segmentation to Discover Behavior Switching in Complex Physical Systems.
Monitoring Stealthy Diffusion.
Discovery of College Students in Financial Hardship.
Accurate Estimation of Generalization Performance for Active Learning.
Knowing an Object by the Company it Keeps: A Domain-Agnostic Scheme for Similarity Discovery.
Exceptionally Monotone Models - The Rank Correlation Model Class for Exceptional Model Mining.
Network Clustering via Maximizing Modularity: Approximation Algorithms and Theoretical Limits.
Jackknifing Documents and Additive Smoothing for Naive Bayes with Scarce Data.
Learning Predictive Substructures with Regularization for Network Data.
Unobtrusive Sensing Incremental Social Contexts Using Fuzzy Class Incremental Learning.
Zhenyu Chen Yiqiang Chen Xingyu Gao Shuangquan Wang Lisha Hu Chenggang Clarence Yan Nicholas D. Lane Chunyan Miao
Modeling Emerging, Evolving and Fading Topics Using Dynamic Soft Orthogonal NMF with Sparse Representation.
Ensemble of Diverse Sparsifications for Link Prediction in Large-Scale Networks.
Towards Frequent Subgraph Mining on Single Large Uncertain Graphs.
Influential Sustainability on Social Networks.
Information Source Detection via Maximum A Posteriori Estimation.
Diamond Sampling for Approximate Maximum All-Pairs Dot-Product (MAD) Search.
Efficient Graphlet Counting for Large Networks.