icdm 2018 论文列表
IEEE International Conference on Data Mining, ICDM 2018, Singapore, November 17-20, 2018.
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Binarized attributed network embedding.
Evaluating Top-k Meta Path Queries on Large Heterogeneous Information Networks.
Density-Adaptive Local Edge Representation Learning with Generative Adversarial Network Multi-label Edge Classification.
Online CP Decomposition for Sparse Tensors.
Forecasting Wavelet Transformed Time Series with Attentive Neural Networks.
Variational Bayesian Inference for Robust Streaming Tensor Factorization and Completion.
Robust Regression via Online Feature Selection Under Adversarial Data Corruption.
Heterogeneous Embedding Propagation for Large-Scale E-Commerce User Alignment.
Layerwise Perturbation-Based Adversarial Training for Hard Drive Health Degree Prediction.
Similarity-Based Active Learning for Image Classification Under Class Imbalance.
A Machine Reading Comprehension-Based Approach for Featured Snippet Extraction.
Neural Sentence-Level Sentiment Classification with Heterogeneous Supervision.
Superlinear Convergence of Randomized Block Lanczos Algorithm.
Feature-Induced Partial Multi-label Learning.
Coherent Graphical Lasso for Brain Network Discovery.
An Integrated Model for Crime Prediction Using Temporal and Spatial Factors.
A Unified Theory of the Mobile Sequential Recommendation Problem.
Adaptive Affinity Learning for Accurate Community Detection.
A Knowledge-Enhanced Deep Recommendation Framework Incorporating GAN-Based Models.
Enhancing Question Understanding and Representation for Knowledge Base Relation Detection.
Exploiting the Sentimental Bias between Ratings and Reviews for Enhancing Recommendation.
Active Learning on Heterogeneous Information Networks: A Multi-armed Bandit Approach.
A TIMBER Framework for Mining Urban Tree Inventories Using Remote Sensing Datasets.
Unsupervised User Identity Linkage via Factoid Embedding.
Prediction of MicroRNA Subcellular Localization by Using a Sequence-to-Sequence Model.
eOTD: An Efficient Online Tucker Decomposition for Higher Order Tensors.
Finding Maximal Significant Linear Representation between Long Time Series.
Uncluttered Domain Sub-Similarity Modeling for Transfer Regression.
Multiple Co-clusterings.
DeepAD: A Deep Learning Based Approach to Stroke-Level Abnormality Detection in Handwritten Chinese Character Recognition.
EPAB: Early Pattern Aware Bayesian Model for Social Content Popularity Prediction.
Partial Multi-view Clustering via Consistent GAN.
Imputing Structured Missing Values in Spatial Data with Clustered Adversarial Matrix Factorization.
Sparse Non-linear CCA through Hilbert-Schmidt Independence Criterion.
Robust Distributed Anomaly Detection Using Optimal Weighted One-Class Random Forests.
Graph Pattern Mining and Learning through User-Defined Relations.
Doc2Cube: Allocating Documents to Text Cube Without Labeled Data.
Entire Regularization Path for Sparse Nonnegative Interaction Model.
Clustered Lifelong Learning Via Representative Task Selection.
Multi-label Adversarial Perturbations.
Record2Vec: Unsupervised Representation Learning for Structured Records.
An Efficient Many-Class Active Learning Framework for Knowledge-Rich Domains.
T2S: Domain Adaptation Via Model-Independent Inverse Mapping and Model Reuse.
Demographic Inference Via Knowledge Transfer in Cross-Domain Recommender Systems.
Tracking and Forecasting Dynamics in Crowdfunding: A Basis-Synthesis Approach.
Predicted Edit Distance Based Clustering of Gene Sequences.
Query-Efficient Black-Box Attack by Active Learning.
Improving Deep Forest by Confidence Screening.
Robust Densest Subgraph Discovery.
Deep Knowledge Tracing and Dynamic Student Classification for Knowledge Tracing.
Spatial Contextualization for Closed Itemset Mining.
Text Segmentation on Multilabel Documents: A Distant-Supervised Approach.
Deep Heterogeneous Autoencoders for Collaborative Filtering.
Leveraging Hypergraph Random Walk Tag Expansion and User Social Relation for Microblog Recommendation.
D-CARS: A Declarative Context-Aware Recommender System.
Deep Discriminative Features Learning and Sampling for Imbalanced Data Problem.
TreeGAN: Syntax-Aware Sequence Generation with Generative Adversarial Networks.
Distribution Preserving Multi-task Regression for Spatio-Temporal Data.
Privacy-Preserving Multi-task Learning.
DOPING: Generative Data Augmentation for Unsupervised Anomaly Detection with GAN.
Transfer Hawkes Processes with Content Information.
Next Point-of-Interest Recommendation with Temporal and Multi-level Context Attention.
Diagnosis Prediction via Medical Context Attention Networks Using Deep Generative Modeling.
Fast Tucker Factorization for Large-Scale Tensor Completion.
Summarizing Graphs at Multiple Scales: New Trends.
Volatility Drift Prediction for Transactional Data Streams.
Time-Discounting Convolution for Event Sequences with Ambiguous Timestamps.
Clustering on Sparse Data in Non-overlapping Feature Space with Applications to Cancer Subtyping.
Mixed Bagging: A Novel Ensemble Learning Framework for Supervised Classification Based on Instance Hardness.
FI-GRL: Fast Inductive Graph Representation Learning via Projection-Cost Preservation.
Interpretable Word Embeddings for Medical Domain.
DeepDiffuse: Predicting the 'Who' and 'When' in Cascades.
Learning Semantic Features for Software Defect Prediction by Code Comments Embedding.
A Harmonic Motif Modularity Approach for Multi-layer Network Community Detection.
Highly Parallel Sequential Pattern Mining on a Heterogeneous Platform.
Confident Kernel Sparse Coding and Dictionary Learning.
Pseudo-Implicit Feedback for Alleviating Data Sparsity in Top-K Recommendation.
Characteristic Subspace Learning for Time Series Classification.
Estimating Latent Relative Labeling Importances for Multi-label Learning.
A Self-Organizing Tensor Architecture for Multi-view Clustering.
A General Cross-Domain Recommendation Framework via Bayesian Neural Network.
Differentially Private Prescriptive Analytics.
Bitcoin Volatility Forecasting with a Glimpse into Buy and Sell Orders.
Multi-view Feature Selection for Heterogeneous Face Recognition.
Multi-level Hypothesis Testing for Populations of Heterogeneous Networks.
DAPPER: Scaling Dynamic Author Persona Topic Model to Billion Word Corpora.
Matrix Profile XII: MPdist: A Novel Time Series Distance Measure to Allow Data Mining in More Challenging Scenarios.
Heterogeneous Data Integration by Learning to Rerank Schema Matches.
SedanSpot: Detecting Anomalies in Edge Streams.
Using Balancing Terms to Avoid Discrimination in Classification.
The HyperKron Graph Model for Higher-Order Features.
Outlier Detection in Urban Traffic Flow Distributions.
Signed Graph Convolutional Networks.
Discovering Topical Interactions in Text-Based Cascades Using Hidden Markov Hawkes Processes.
Dynamic Illness Severity Prediction via Multi-task RNNs for Intensive Care Unit.
Semi-Convex Hull Tree: Fast Nearest Neighbor Queries for Large Scale Data on GPUs.
Cost Effective Multi-label Active Learning via Querying Subexamples.
DrugCom: Synergistic Discovery of Drug Combinations Using Tensor Decomposition.
Exploiting Spatio-Temporal Correlations with Multiple 3D Convolutional Neural Networks for Citywide Vehicle Flow Prediction.
A Variable-Order Regime Switching Model to Identify Significant Patterns in Financial Markets.
Accurate Causal Inference on Discrete Data.
Heterogeneous Hyper-Network Embedding.
Semi-Supervised Community Detection Using Structure and Size.
Maximizing the Diversity of Exposure in a Social Network.
NetGist: Learning to Generate Task-Based Network Summaries.
Fast Rectangle Counting on Massive Networks.
Matrix Profile XI: SCRIMP++: Time Series Motif Discovery at Interactive Speeds.
Independent Feature and Label Components for Multi-label Classification.
Dynamic Truth Discovery on Numerical Data.
Deep Learning Based Scalable Inference of Uncertain Opinions.
Zero-Shot Learning: An Energy Based Approach.
Billion-Scale Network Embedding with Iterative Random Projection.
Chinese Medical Concept Normalization by Using Text and Comorbidity Network Embedding.
Integrative Analysis of Patient Health Records and Neuroimages via Memory-Based Graph Convolutional Network.
CADEN: A Context-Aware Deep Embedding Network for Financial Opinions Mining.
Image-Enhanced Multi-level Sentence Representation Net for Natural Language Inference.
SINE: Scalable Incomplete Network Embedding.
Adversarially Learned Anomaly Detection.
MuVAN: A Multi-view Attention Network for Multivariate Temporal Data.
Online Dictionary Learning with Confidence.
DE-RNN: Forecasting the Probability Density Function of Nonlinear Time Series.
Collapsed Variational Inference for Nonparametric Bayesian Group Factor Analysis.
LEEM: Lean Elastic EM for Gaussian Mixture Model via Bounds-Based Filtering.
Towards Interpretation of Recommender Systems with Sorted Explanation Paths.
Meta-Graph Based HIN Spectral Embedding: Methods, Analyses, and Insights.
Dr. Right!: Embedding-Based Adaptively-Weighted Mixture Multi-classification Model for Finding Right Doctors with Healthcare Experience Data.
Robust Cascade Reconstruction by Steiner Tree Sampling.
A Low Rank Weighted Graph Convolutional Approach to Weather Prediction.
Deep Reinforcement Learning with Knowledge Transfer for Online Rides Order Dispatching.
Bug Localization via Supervised Topic Modeling.
Exploiting Topic-Based Adversarial Neural Network for Cross-Domain Keyphrase Extraction.
A Reinforcement Learning Framework for Explainable Recommendation.
ASTM: An Attentional Segmentation Based Topic Model for Short Texts.
Deep Structure Learning for Fraud Detection.
A United Approach to Learning Sparse Attributed Network Embedding.
Human-Centric Urban Transit Evaluation and Planning.
Incomplete Label Uncertainty Estimation for Petition Victory Prediction with Dynamic Features.
Semi-Supervised Anomaly Detection with an Application to Water Analytics.
Multi-label Answer Aggregation Based on Joint Matrix Factorization.
The Impact of Environmental Stressors on Human Trafficking.
Interactive Unknowns Recommendation in E-Learning Systems.
A Blended Deep Learning Approach for Predicting User Intended Actions.
Multi-task Sparse Metric Learning for Monitoring Patient Similarity Progression.
Deep Headline Generation for Clickbait Detection.
GINA: Group Gender Identification Using Privacy-Sensitive Audio Data.
Synthetic Oversampling with the Majority Class: A New Perspective on Handling Extreme Imbalance.
Multi-label Learning with Label Enhancement.
Local Low-Rank Hawkes Processes for Temporal User-Item Interactions.
ProSecCo: Progressive Sequence Mining with Convergence Guarantees.
DipTransformation: Enhancing the Structure of a Dataset and Thereby Improving Clustering.
Finding Events in Temporal Networks: Segmentation Meets Densest-Subgraph Discovery.
SuperPart: Supervised Graph Partitioning for Record Linkage.
Privacy-Preserving Temporal Record Linkage.
Collaborative Translational Metric Learning.
Apk2vec: Semi-Supervised Multi-view Representation Learning for Profiling Android Applications.
Maximally Consistent Sampling and the Jaccard Index of Probability Distributions.
Intelligent Salary Benchmarking for Talent Recruitment: A Holistic Matrix Factorization Approach.
Tell me Something My Friends do not Know: Diversity Maximization in Social Networks.
Discovering Reliable Dependencies from Data: Hardness and Improved Algorithms.
ResumeNet: A Learning-Based Framework for Automatic Resume Quality Assessment.
Collective Human Behavior in Cascading System: Discovery, Modeling and Applications.
Enhancing Very Fast Decision Trees with Local Split-Time Predictions.
A Semi-Supervised and Inductive Embedding Model for Churn Prediction of Large-Scale Mobile Games.
Concept Mining via Embedding.
Accelerating Experimental Design by Incorporating Experimenter Hunches.
SSDMV: Semi-Supervised Deep Social Spammer Detection by Multi-view Data Fusion.
Summarizing Network Processes with Network-Constrained Boolean Matrix Factorization.
Fast Single-Class Classification and the Principle of Logit Separation.
Utilizing In-store Sensors for Revisit Prediction.
Explainable Time Series Tweaking via Irreversible and Reversible Temporal Transformations.
Self-Attentive Sequential Recommendation.
Cross-Domain Labeled LDA for Cross-Domain Text Classification.
Representing Networks with 3D Shapes.
Asynchronous Dual Free Stochastic Dual Coordinate Ascent for Distributed Data Mining.
dpMood: Exploiting Local and Periodic Typing Dynamics for Personalized Mood Prediction.
EDLT: Enabling Deep Learning for Generic Data Classification.
Defending Against Adversarial Samples Without Security through Obscurity.
Learning Sequential Behavior Representations for Fraud Detection.
Deep Semantic Correlation Learning Based Hashing for Multimedia Cross-Modal Retrieval.
Hierarchical Hybrid Feature Model for Top-N Context-Aware Recommendation.
Probabilistic Streaming Tensor Decomposition.
Sequential Pattern Sampling with Norm Constraints.
Imbalanced Augmented Class Learning with Unlabeled Data by Label Confidence Propagation.
Learning Community Structure with Variational Autoencoder.
Rational Neural Networks for Approximating Graph Convolution Operator on Jump Discontinuities.
TADA: Trend Alignment with Dual-Attention Multi-task Recurrent Neural Networks for Sales Prediction.
Prerequisite-Driven Deep Knowledge Tracing.
Social Recommendation with Missing Not at Random Data.
Realization of Random Forest for Real-Time Evaluation through Tree Framing.
On Multi-query Local Community Detection.
Which Outlier Detector Should I use?
Discourse Processing and Its Applications in Text Mining.
Blockchain Data Analytics.
Automatic Optical Coherence Tomography Imaging Analysis for Retinal Disease Screening Using Machine Learning Techniques.
Landscape of Practical Blockchain Systems and their Applications.
On Big Wisdom.
