SIGKDD(KDD) 2015 论文列表
Proceedings of the 21th ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, Sydney, NSW, Australia, August 10-13, 2015.
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Data Driven Science: SIGKDD Panel.
Big Data Analytics: Optimization and Randomization.
Medical Mining: KDD 2015 Tutorial.
Large Scale Distributed Data Science using Apache Spark.
VC-Dimension and Rademacher Averages: From Statistical Learning Theory to Sampling Algorithms.
Automatic Entity Recognition and Typing from Massive Text Corpora: A Phrase and Network Mining Approach.
Social Media Anomaly Detection: Challenges and Solutions.
Diffusion in Social and Information Networks: Research Problems, Probabilistic Models and Machine Learning Methods.
Dense Subgraph Discovery: KDD 2015 tutorial.
Data-Driven Product Innovation.
Graph-Based User Behavior Modeling: From Prediction to Fraud Detection.
Web Personalization and Recommender Systems.
Predicting Ambulance Demand: a Spatio-Temporal Kernel Approach.
Stock Constrained Recommendation in Tmall.
Building Discriminative User Profiles for Large-scale Content Recommendation.
Forecasting Fine-Grained Air Quality Based on Big Data.
Annotating Needles in the Haystack without Looking: Product Information Extraction from Emails.
Gas Concentration Reconstruction for Coal-Fired Boilers Using Gaussian Process.
Tornado Forecasting with Multiple Markov Boundaries.
From Infrastructure to Culture: A/B Testing Challenges in Large Scale Social Networks.
Smart Pacing for Effective Online Ad Campaign Optimization.
Predicting Serves in Tennis using Style Priors.
Discerning Tactical Patterns for Professional Soccer Teams: An Enhanced Topic Model with Applications.
Client Clustering for Hiring Modeling in Work Marketplaces.
Interpreting Advertiser Intent in Sponsored Search.
Efficient Long-Term Degradation Profiling in Time Series for Complex Physical Systems.
FrauDetector: A Graph-Mining-based Framework for Fraudulent Phone Call Detection.
Transfer Learning for Bilingual Content Classification.
Mining for Causal Relationships: A Data-Driven Study of the Islamic State.
When-To-Post on Social Networks.
Early Prediction of Cardiac Arrest (Code Blue) using Electronic Medical Records.
Going In-Depth: Finding Longform on the Web.
Effective Audience Extension in Online Advertising.
Spoken English Grading: Machine Learning with Crowd Intelligence.
Early Identification of Violent Criminal Gang Members.
Scalable Machine Learning Approaches for Neighborhood Classification Using Very High Resolution Remote Sensing Imagery.
An Architecture for Agile Machine Learning in Real-Time Applications.
Proof Protocol for a Machine Learning Technique Making Longitudinal Predictions in Dynamic Contexts.
Predictive Modeling for Public Health: Preventing Childhood Lead Poisoning.
Learning a Hierarchical Monitoring System for Detecting and Diagnosing Service Issues.
Predicting Future Scientific Discoveries Based on a Networked Analysis of the Past Literature.
Analyzing Invariants in Cyber-Physical Systems using Latent Factor Regression.
Voltage Correlations in Smart Meter Data.
Distributed Personalization.
Discovery of Glaucoma Progressive Patterns Using Hierarchical MDL-Based Clustering.
Predicting Voice Elicited Emotions.
Click-through Prediction for Advertising in Twitter Timeline.
Leveraging Knowledge Bases for Contextual Entity Exploration.
Generic and Scalable Framework for Automated Time-series Anomaly Detection.
Promoting Positive Post-Click Experience for In-Stream Yahoo Gemini Users.
Probabilistic Graphical Models of Dyslexia.
A Machine Learning Framework to Identify Students at Risk of Adverse Academic Outcomes.
Discovering Collective Narratives of Theme Parks from Large Collections of Visitors' Photo Streams.
Visual Search at Pinterest.
Life-stage Prediction for Product Recommendation in E-commerce.
Real-Time Bid Prediction using Thompson Sampling-Based Expert Selection.
Traffic Measurement and Route Recommendation System for Mass Rapid Transit (MRT).
Focusing on the Long-term: It's Good for Users and Business.
Measuring Causal Impact of Online Actions via Natural Experiments: Application to Display Advertising.
Mining Administrative Data to Spur Urban Revitalization.
Gender and Interest Targeting for Sponsored Post Advertising at Tumblr.
E-commerce in Your Inbox: Product Recommendations at Scale.
On the Reliability of Profile Matching Across Large Online Social Networks.
One-Pass Ranking Models for Low-Latency Product Recommendations.
Utilizing Text Mining on Online Medical Forums to Predict Label Change due to Adverse Drug Reactions.
Collective Spammer Detection in Evolving Multi-Relational Social Networks.
Online Topic-based Social Influence Analysis for the Wimbledon Championships.
Probabilistic Modeling of a Sales Funnel to Prioritize Leads.
Big Data System for Analyzing Risky Procurement Entities.
User Conditional Hashtag Prediction for Images.
Intelligible Models for HealthCare: Predicting Pneumonia Risk and Hospital 30-day Readmission.
Multi-View Incident Ticket Clustering for Optimal Ticket Dispatching.
ALOJA-ML: A Framework for Automating Characterization and Knowledge Discovery in Hadoop Deployments.
Dynamic Hierarchical Classification for Patient Risk-of-Readmission.
Predictive Approaches for Low-Cost Preventive Medicine Program in Developing Countries.
Exploiting Data Mining for Authenticity Assessment and Protection of High-Quality Italian Wines from Piedmont.
Whither Social Networks for Web Search?
Personalizing LinkedIn Feed.
The Effectiveness of Marketing Strategies in Social Media: Evidence from Promotional Events.
User Modeling in Telecommunications and Internet Industry.
Data Science from the Lab to the Field to the Enterprise.
Clouded Intelligence.
Powering Real-time Decision Engines in Finance and Healthcare using Open Source Software.
Optimizing Marketing Impact through Data Driven Decisioning.
How Artificial Intelligence and Big Data Created Rocket Fuel: A Case Study.
Data Science at Visa.
Should You Trust Your Money to a Robot?
Hadoop's Impact on the Future of Data Management.
Scaling Machine Learning and Statistics for Web Applications.
Query Workloads for Data Series Indexes.
Debiasing Crowdsourced Batches.
Co-Clustering based Dual Prediction for Cargo Pricing Optimization.
Modeling User Mobility for Location Promotion in Location-based Social Networks.
Integrating Vertex-centric Clustering with Edge-centric Clustering for Meta Path Graph Analysis.
Cuckoo Linear Algebra.
Modeling Truth Existence in Truth Discovery.
L∞ Error and Bandwidth Selection for Kernel Density Estimates of Large Data.
Linear Time Samplers for Supervised Topic Models using Compositional Proposals.
SEISMIC: A Self-Exciting Point Process Model for Predicting Tweet Popularity.
Multi-Task Learning for Spatio-Temporal Event Forecasting.
SAME but Different: Fast and High Quality Gibbs Parameter Estimation.
COSNET: Connecting Heterogeneous Social Networks with Local and Global Consistency.
Deep Model Based Transfer and Multi-Task Learning for Biological Image Analysis.
Statistical Arbitrage Mining for Display Advertising.
A Collective Bayesian Poisson Factorization Model for Cold-start Local Event Recommendation.
Panther: Fast Top-k Similarity Search on Large Networks.
Organizational Chart Inference.
Dynamic Topic Modeling for Monitoring Market Competition from Online Text and Image Data.
Assembler: Efficient Discovery of Spatial Co-evolving Patterns in Massive Geo-sensory Data.
An Efficient Semi-Supervised Clustering Algorithm with Sequential Constraints.
Entity Matching across Heterogeneous Sources.
Structural Graphical Lasso for Learning Mouse Brain Connectivity.
Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning.
Deep Graph Kernels.
Performance Modeling and Scalability Optimization of Distributed Deep Learning Systems.
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction.
Petuum: A New Platform for Distributed Machine Learning on Big Data.
Edge-Weighted Personalized PageRank: Breaking A Decade-Old Performance Barrier.
Diversifying Restricted Boltzmann Machine for Document Modeling.
Predicting Winning Price in Real Time Bidding with Censored Data.
Cinema Data Mining: The Smell of Fear.
Dynamic Poisson Autoregression for Influenza-Like-Illness Case Count Prediction.
Regularity and Conformity: Location Prediction Using Heterogeneous Mobility Data.
Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics.
Geo-SAGE: A Geographical Sparse Additive Generative Model for Spatial Item Recommendation.
Trading Interpretability for Accuracy: Oblique Treed Sparse Additive Models.
Collaborative Deep Learning for Recommender Systems.
Towards Interactive Construction of Topical Hierarchy: A Recursive Tensor Decomposition Approach.
Incorporating World Knowledge to Document Clustering via Heterogeneous Information Networks.
Deep Learning Architecture with Dynamically Programmed Layers for Brain Connectome Prediction.
Discovering Valuable items from Massive Data.
Scaling Up Stochastic Dual Coordinate Ascent.
An Effective Marketing Strategy for Revenue Maximization with a Quantity Constraint.
PTE: Predictive Text Embedding through Large-scale Heterogeneous Text Networks.
Transitive Transfer Learning.
LINKAGE: An Approach for Comprehensive Risk Prediction for Care Management.
Exploiting Relevance Feedback in Knowledge Graph Search.
Set Cover at Web Scale.
Turn Waste into Wealth: On Simultaneous Clustering and Cleaning over Dirty Data.
Efficient Latent Link Recommendation in Signed Networks.
An Evaluation of Parallel Eccentricity Estimation Algorithms on Undirected Real-World Graphs.
Discovery of Meaningful Rules in Time Series.
Community Detection based on Distance Dynamics.
Inside Jokes: Identifying Humorous Cartoon Captions.
TimeCrunch: Interpretable Dynamic Graph Summarization.
Bayesian Poisson Tensor Factorization for Inferring Multilateral Relations from Sparse Dyadic Event Counts.
Stochastic Divergence Minimization for Online Collapsed Variational Bayes Zero Inference of Latent Dirichlet Allocation.
Matrix Completion with Queries.
Why It Happened: Identifying and Modeling the Reasons of the Happening of Social Events.
Mining Frequent Itemsets through Progressive Sampling with Rademacher Averages.
ClusType: Effective Entity Recognition and Typing by Relation Phrase-Based Clustering.
Collective Opinion Spam Detection: Bridging Review Networks and Metadata.
Virus Propagation in Multiple Profile Networks.
Locally Densest Subgraph Discovery.
SCRAM: A Sharing Considered Route Assignment Mechanism for Fair Taxi Route Recommendations.
State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness.
A PCA-Based Change Detection Framework for Multidimensional Data Streams: Change Detection in Multidimensional Data Streams.
Subspace Clustering Using Log-determinant Rank Approximation.
Discovering and Exploiting Deterministic Label Relationships in Multi-Label Learning.
Optimal Kernel Group Transformation for Exploratory Regression Analysis and Graphics.
Non-transitive Hashing with Latent Similarity Components.
Quick Sensitivity Analysis for Incremental Data Modification and Its Application to Leave-one-out CV in Linear Classification Problems.
Efficient PageRank Tracking in Evolving Networks.
Fast and Robust Parallel SGD Matrix Factorization.
Simultaneous Modeling of Multiple Diseases for Mortality Prediction in Acute Hospital Care.
Extreme States Distribution Decomposition Method for Search Engine Online Evaluation.
Flexible and Robust Multi-Network Clustering.
Graph Query Reformulation with Diversity.
Scalable Large Near-Clique Detection in Large-Scale Networks via Sampling.
Data-Driven Activity Prediction: Algorithms, Evaluation Methodology, and Applications.
Inferring Networks of Substitutable and Complementary Products.
Robust Treecode Approximation for Kernel Machines.
Dimensionality Reduction Via Graph Structure Learning.
Algorithmic Cartography: Placing Points of Interest and Ads on Maps.
FaitCrowd: Fine Grained Truth Discovery for Crowdsourced Data Aggregation.
Influence at Scale: Distributed Computation of Complex Contagion in Networks.
Fast and Memory-Efficient Significant Pattern Mining via Permutation Testing.
Spectral Ensemble Clustering.
Temporal Phenotyping from Longitudinal Electronic Health Records: A Graph Based Framework.
A Learning-based Framework to Handle Multi-round Multi-party Influence Maximization on Social Networks.
MASCOT: Memory-efficient and Accurate Sampling for Counting Local Triangles in Graph Streams.
On the Discovery of Evolving Truth.
0-Bit Consistent Weighted Sampling.
The Child is Father of the Man: Foresee the Success at the Early Stage.
Online Influence Maximization.
Maximum Likelihood Postprocessing for Differential Privacy under Consistency Constraints.
Reducing the Unlabeled Sample Complexity of Semi-Supervised Multi-View Learning.
Unified and Contrasting Cuts in Multiple Graphs: Application to Medical Imaging Segmentation.
VEWS: A Wikipedia Vandal Early Warning System.
From Group to Individual Labels Using Deep Features.
TOPTRAC: Topical Trajectory Pattern Mining.
A Decision Tree Framework for Spatiotemporal Sequence Prediction.
Simultaneous Discovery of Common and Discriminative Topics via Joint Nonnegative Matrix Factorization.
On Estimating the Swapping Rate for Categorical Data.
Towards Decision Support and Goal Achievement: Identifying Action-Outcome Relationships From Social Media.
Real Time Recommendations from Connoisseurs.
Scalable Blocking for Privacy Preserving Record Linkage.
Leveraging Social Context for Modeling Topic Evolution.
Deep Computational Phenotyping.
Accelerated Alternating Direction Method of Multipliers.
Improved Bounds on the Dot Product under Random Projection and Random Sign Projection.
Structured Hedging for Resource Allocations with Leverage.
Learning with Similarity Functions on Graphs using Matchings of Geometric Embeddings.
Reciprocity in Social Networks with Capacity Constraints.
Website Optimization Problem and Its Solutions.
Inferring Air Quality for Station Location Recommendation Based on Urban Big Data.
Non-exhaustive, Overlapping Clustering via Low-Rank Semidefinite Programming.
Real-Time Top-R Topic Detection on Twitter with Topic Hijack Filtering.
Probabilistic Community and Role Model for Social Networks.
Learning Tree Structure in Multi-Task Learning.
Network Lasso: Clustering and Optimization in Large Graphs.
A Deep Hybrid Model for Weather Forecasting.
Instance Weighting for Patient-Specific Risk Stratification Models.
Using Local Spectral Methods to Robustify Graph-Based Learning Algorithms.
Selective Hashing: Closing the Gap between Radius Search and k-NN Search.
Anatomical Annotations for Drosophila Gene Expression Patterns via Multi-Dimensional Visual Descriptors Integration: Multi-Dimensional Feature Learning.
Reconstructing Textual Documents from n-grams.
Monitoring Least Squares Models of Distributed Streams.
Adaptive Message Update for Fast Affinity Propagation.
Real Estate Ranking via Mixed Land-use Latent Models.
Who Supported Obama in 2012?: Ecological Inference through Distribution Regression.
A Clustering-Based Framework to Control Block Sizes for Entity Resolution.
RSC: Mining and Modeling Temporal Activity in Social Media.
Certifying and Removing Disparate Impact.
More Constraints, Smaller Coresets: Constrained Matrix Approximation of Sparse Big Data.
Hierarchical Graph-Coupled HMMs for Heterogeneous Personalized Health Data.
Beyond Triangles: A Distributed Framework for Estimating 3-profiles of Large Graphs.
Dirichlet-Hawkes Processes with Applications to Clustering Continuous-Time Document Streams.
Unsupervised Feature Selection with Adaptive Structure Learning.
CoupledLP: Link Prediction in Coupled Networks.
Dynamic Matrix Factorization with Priors on Unknown Values.
Optimal Action Extraction for Random Forests and Boosted Trees.
Adaptation Algorithm and Theory Based on Generalized Discrepancy.
Stream Sampling for Frequency Cap Statistics.
Warm Start for Parameter Selection of Linear Classifiers.
Efficient Algorithms for Public-Private Social Networks.
Differentially Private High-Dimensional Data Publication via Sampling-Based Inference.
Heterogeneous Network Embedding via Deep Architectures.
On the Formation of Circles in Co-authorship Networks.
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification.
Online Outlier Exploration Over Large Datasets.
Facets: Fast Comprehensive Mining of Coevolving High-order Time Series.
Dynamically Modeling Patient's Health State from Electronic Medical Records: A Time Series Approach.
Efficient Online Evaluation of Big Data Stream Classifiers.
Accelerating Dynamic Time Warping Clustering with a Novel Admissible Pruning Strategy.
Portraying Collective Spatial Attention in Twitter.
Estimating Local Intrinsic Dimensionality.
TimeMachine: Timeline Generation for Knowledge-Base Entities.
Large-Scale Distributed Bayesian Matrix Factorization using Stochastic Gradient MCMC.
Data, Knowledge and Discovery: Machine Learning meets Natural Science.
Machine Learning and Causal Inference for Policy Evaluation.
MOOCS: What Have We Learned?
Online Controlled Experiments: Lessons from Running A/B/n Tests for 12 Years.
