yusuke1997/dblp-id-title huggingface dataset:
Pictor: an interactive system for importing data from a website
Online Quality Prediction in Windshield Manufacturing using Data-Efficient Machine Learning
Automatic Phenotyping by a Seed-guided Topic Model
A system to grade computer programming skills using machine learning
Experience from hosting a corporate prediction market: benefits beyond the forecasts
Privacy in Advertising: Analytics and Modeling
Proceedings of the Thirteenth International Workshop on Multimedia Data Mining, MDMKDD 2013, Chicago, Illinois, USA, August 11, 2013
Optimizing Long-Term Efficiency and Fairness in Ride-Hailing via Joint Order Dispatching and Driver Repositioning
CERAM: Coverage Expansion for Recommendations by Associating Discarded Models
Learning Structural Node Embeddings via Diffusion Wavelets
Large Language Models meet Collaborative Filtering: An Efficient All-round LLM-based Recommender System
Understanding the Ranking Loss for Recommendation with Sparse User Feedback
Architecture and Operation Adaptive Network for Online Recommendations
Towards Confidence in the Truth: A Bootstrapping based Truth Discovery Approach
Fast rank-2 nonnegative matrix factorization for hierarchical document clustering
The Third International TrueFact Workshop: Making a Credible Web for Tomorrow
Breaking the Memory Wall for Heterogeneous Federated Learning via Progressive Training
Web Usage Mining by Means of Multidimensional Sequence Alignment Methods
Multi-class cost-sensitive boosting with p-norm loss functions
The Minimum Informative Subset Problem
Causal Inference and Machine Learning in Practice with EconML and CausalML: Industrial Use Cases at Microsoft, TripAdvisor, Uber
Adaptive Multi-view Rule Discovery for Weakly-Supervised Compatible Products Prediction
Information awareness: a prospective technical assessment
Semantic Content-Based Retrieval in a Video Database
Multimodal Indoor Localisation in Parkinson's Disease for Detecting Medication Use: Observational Pilot Study in a Free-Living Setting
An Innovative Concept for Image Information Mining
Detecting outliers using transduction and statistical testing
Web mining from competitors' websites
Multi-Behavior Collaborative Filtering with Partial Order Graph Convolutional Networks
Accurate and Fast Asymmetric Locality-Sensitive Hashing Scheme for Maximum Inner Product Search
Accurate Node Feature Estimation with Structured Variational Graph Autoencoder
Leveraging Exposure Networks for Detecting Fake News Sources
Why Not Together? A Multiple-Round Recommender System for Queries and Items
Designing crowdsourcing community for the enterprise
Random forests for metric learning with implicit pairwise position dependence
Matching users and items across domains to improve the recommendation quality
FlowXpert: Expertizing Troubleshooting Workflow Orchestration with Knowledge Base and Multi-Agent Coevolution
Model-based Clustering of Short Text Streams
Mitigating Data Imbalance in Time Series Classification Based on Counterfactual Minority Samples Augmentation
Self-Supervised Hypergraph Transformer for Recommender Systems
Predictors without Borders: Behavioral Modeling of Product Adoption in Three Developing Countries
Sensing places' life to make city smarter
OptMatch: Optimized Matchmaking via Modeling the High-Order Interactions on the Arena
User-Event Graph Embedding Learning for Context-Aware Recommendation
Type Linking for Query Understanding and Semantic Search
Predicting Long-term Dynamics of Complex Networks via Identifying Skeleton in Hyperbolic Space
Explainability for Natural Language Processing
UoMo: A Universal Model of Mobile Traffic Forecasting for Wireless Network Optimization
Meta-path based multi-network collective link prediction
Mining periodic behaviors for moving objects
Interpretable Representation Learning for Healthcare via Capturing Disease Progression through Time
ERASE: Benchmarking Feature Selection Methods for Deep Recommender Systems
A Survey on Hypergraph Neural Networks: An In-Depth and Step-By-Step Guide
Towards Optimal Execution of Density-based Clustering on Heterogeneous Hardware
Search war: a game for improving web search
Unsupervised Feature Selection in Signed Social Networks
Efficient and Effective Anchored Densest Subgraph Search: A Convex-programming based Approach
A Dirty Dozen: Twelve Common Metric Interpretation Pitfalls in Online Controlled Experiments
FISM: factored item similarity models for top-N recommender systems
Finding Gangs in War from Signed Networks
Keynote Speaker: Emery N. Brown
CATER: A Cluster-Based Alternative-Term Recommendation Framework for Large-Scale Web Search at NAVER
When Recommendation Goes Wrong: Anomalous Link Discovery in Recommendation Networks
Multi-task Offline Reinforcement Learning for Online Advertising in Recommender Systems
4th Workshop on Uncertainty Reasoning and Quantification in Decision Making (UDM)
Modeling impression discounting in large-scale recommender systems
Canonicalization of database records using adaptive similarity measures
MBrain: A Multi-channel Self-Supervised Learning Framework for Brain Signals
Tackling Instance-Dependent Label Noise with Class Rebalance and Geometric Regularization
Growing a tree in the forest: constructing folksonomies by integrating structured metadata
UCPhrase: Unsupervised Context-aware Quality Phrase Tagging
Structural Deep Brain Network Mining
A Geometric Approach to Predicting Bounds of Downstream Model Performance
Parallel Graph Mining with GPUs
Metapattern Generation for Integrated Data Mining
Cut-and-stitch: efficient parallel learning of linear dynamical systems on smps
A High Performance Implementation of the Data Space Transfer Protocol (DSTP)
Probabilistic Gradient Boosting Machines for Large-Scale Probabilistic Regression
Integrating Domain-Knowledge into Deep Learning
KATE: K-Competitive Autoencoder for Text
A Permutation Approach to Assess Confounding in Machine Learning Applications for Digital Health
A system for real-time competitive market intelligence
Antibody Complementarity Determining Regions (CDRs) design using Constrained Energy Model
Learning Universal Multi-level Market Irrationality Factors to Improve Stock Return Forecasting
Local Boosting for Weakly-Supervised Learning
Cyclic pattern kernels for predictive graph mining
On the discovery of significant statistical quantitative rules
Spectral Clustering of Attributed Multi-relational Graphs
JiuZhang: A Chinese Pre-trained Language Model for Mathematical Problem Understanding
Data Mining for Direct Marketing: Problems and Solutions
PARSIFAL: Private and Robust Sign Federated Learning
Collaborative Knowledge Base Embedding for Recommender Systems
Genre-based decomposition of email class noise
NPA: Neural News Recommendation with Personalized Attention
Addressing Challenges in Data Science: Scale, Skill Sets and Complexity
Operational security analytics: doing more with less
Contextual Spatial Outlier Detection with Metric Learning
Hierarchical Knowledge Guided Fault Intensity Diagnosis of Complex Industrial Systems
SkySearch: Satellite Video Search at Scale
Multi-Pointer Co-Attention Networks for Recommendation
ProGAN: Network Embedding via Proximity Generative Adversarial Network
Applying Data Mining and Machine Learning Techniques to Submarine Intelligence Analysis
Quantifying Node Importance over Network Structural Stability
Deep Representations for Time-varying Brain Datasets
LogParser-LLM: Advancing Efficient Log Parsing with Large Language Models
Model Multiple Heterogeneity via Hierarchical Multi-Latent Space Learning
Improving the modified nyström method using spectral shifting
Retrieval-Based Gradient Boosting Decision Trees for Disease Risk Assessment
Learning to Predict the Duration of an Automobile Trip
Mining coherent gene clusters from gene-sample-time microarray data
Fake News Research: Theories, Detection Strategies, and Open Problems
Exploring Student Check-In Behavior for Improved Point-of-Interest Prediction
Optimal Dynamic Subset Sampling: Theory and Applications
Would Your Tweet Invoke Hate on the Fly? Forecasting Hate Intensity of Reply Threads on Twitter
An Unsupervised Learning Framework Combined with Heuristics for the Maximum Minimal Cut Problem
Learning to detect malicious executables in the wild
Generalizable Low-Resource Activity Recognition with Diverse and Discriminative Representation Learning
Incrementally optimized decision tree for noisy big data
On Post-selection Inference in A/B Testing
Human-In-The-Loop Topic Discovery with Embedded Text Representations
Deep Bayesian Mining, Learning and Understanding
Mining and summarizing customer reviews
Multi-Task Feature Interaction Learning
A Dataset Decomposition Approach to Data Mining and Machine Discovery
End-to-End Inventory Prediction and Contract Allocation for Guaranteed Delivery Advertising
RelKD 2023: International Workshop on Resource-Efficient Learning for Knowledge Discovery
The Legislative Influence Detector: Finding Text Reuse in State Legislation
Graph Contrastive Learning with Generative Adversarial Network
Predicting Matchups and Preferences in Context
Name Disambiguation in AMiner: Clustering, Maintenance, and Human in the Loop
STED: semi-supervised targeted-interest event detectionin in twitter
Statistical Models Coupling Allows for Complex Local Multivariate Time Series Analysis
Distributed Thresholded Counting with Limited Interaction
Practical guide to controlled experiments on the web: listen to your customers not to the hippo
Constructing and Mining Heterogeneous Information Networks from Massive Text
Generalizable Recommender System During Temporal Popularity Distribution Shifts
Ranking with Slot Constraints
Big Data Needs Big Dreamers: Lessons from Successful Big Data Investors
Growing decision trees on support-less association rules
Welfare Maximization in Online Two-sided Marketplaces
Incremental approximate matrix factorization for speeding up support vector machines
SGD-DyG: Self-Reliant Global Dependency Apprehending on Dynamic Graphs
An empirical study of reserve price optimisation in real-time bidding
HiFGL: A Hierarchical Framework for Cross-silo Cross-device Federated Graph Learning
Time Matters: Enhancing Sequential Recommendations with Time-Guided Graph Neural ODEs
Interview Choice Reveals Your Preference on the Market: To Improve Job-Resume Matching through Profiling Memories
Exact and Consistent Interpretation for Piecewise Linear Neural Networks: A Closed Form Solution
Differential identifiability
PittGrub: A Frustration-Free System to Reduce Food Waste by Notifying Hungry College Students
Fast Unsupervised Online Drift Detection Using Incremental Kolmogorov-Smirnov Test
Key semantics extraction by dependency tree mining
Optimizing Traffic Control with Model-Based Learning: A Pessimistic Approach to Data-Efficient Policy Inference
FLea: Addressing Data Scarcity and Label Skew in Federated Learning via Privacy-preserving Feature Augmentation
Automatic Categorization of Web Pages and User Clustering with Mixtures of Hidden Markov Models
Energy-Efficient Models for High-Dimensional Spike Train Classification using Sparse Spiking Neural Networks
Discovering interesting patterns through user's interactive feedback
Question-Driven eXplainable AI: Re-framing the Technical and Design Spaces of XAI
Anomaly and Novelty Detection, Explanation, and Accommodation (ANDEA)
AdaTT: Adaptive Task-to-Task Fusion Network for Multitask Learning in Recommendations
Beyond keyword search: discovering relevant scientific literature
Multi-layer Representation Learning for Medical Concepts
Predicting long-term impact of CQA posts: a comprehensive viewpoint
Fairness in Streaming Submodular Maximization Subject to a Knapsack Constraint
ReLoop2: Building Self-Adaptive Recommendation Models via Responsive Error Compensation Loop
A Sublinear Time Algorithm for Opinion Optimization in Directed Social Networks via Edge Recommendation
Visualization and the process of modeling: a cognitive-theoretic view
Hyper-Local Deformable Transformers for Text Spotting on Historical Maps
Dynamic Recommendations for Sequential Hiring Decisions in Online Labor Markets
Selection, combination, and evaluation of effective software sensors for detecting abnormal computer usage
Direct local pattern sampling by efficient two-step random procedures
BadSampler: Harnessing the Power of Catastrophic Forgetting to Poison Byzantine-robust Federated Learning
AKUPM: Attention-Enhanced Knowledge-Aware User Preference Model for Recommendation
Making recommendations from multiple domains
Offline Reinforcement Learning for Optimizing Production Bidding Policies
Extreme Multi-label Loss Functions for Recommendation, Tagging, Ranking & Other Missing Label Applications
Generating Long Semantic IDs in Parallel for Recommendation
Dynamic Causal Structure Discovery and Causal Effect Estimation
Reinforcement Subgraph Reasoning for Fake News Detection
On Aligning Tuples for Regression
A Broader Picture of Random-walk Based Graph Embedding
Root Cause Analysis for Microservice Systems via Hierarchical Reinforcement Learning from Human Feedback
Discriminant Adaptive Nearest Neighbor Classification
Approximate graph mining with label costs
Asymmetric support vector machines: low false-positive learning under the user tolerance
Robust Graph Convolutional Networks Against Adversarial Attacks
Accelerated Alternating Direction Method of Multipliers
Recommendation in social media: recent advances and new frontiers
COA: finding novel patents through text analysis
Equity, Diversity & Inclusion (EDI): Special Day at ACM KDD 2024
UniST: A Prompt-Empowered Universal Model for Urban Spatio-Temporal Prediction
Generalized Zero-Shot Extreme Multi-label Learning
Binary Embedding-based Retrieval at Tencent
Mining event periodicity from incomplete observations
Applying the Delta Method in Metric Analytics: A Practical Guide with Novel Ideas
Proceedings of the 31st ACM SIGKDD Conference on Knowledge Discovery and Data Mining, V.1, KDD 2025, Toronto, ON, Canada, August 3-7, 2025
Multimedia data mining (workshop session - title only)
DeepUrbanEvent: A System for Predicting Citywide Crowd Dynamics at Big Events
CFI-Stream: mining closed frequent itemsets in data streams
Learning from History and Present: Next-item Recommendation via Discriminatively Exploiting User Behaviors
ST-Norm: Spatial and Temporal Normalization for Multi-variate Time Series Forecasting
Towards Understanding and Enhancing Robustness of Deep Learning Models against Malicious Unlearning Attacks
Fitbit for Chickens?: Time Series Data Mining Can Increase the Productivity of Poultry Farms
The Second Workshop on Knowledge-Augmented Methods for Natural Language Processing
IntelliClean: a knowledge-based intelligent data cleaner
Graph Attention Networks over Edge Content-Based Channels
Online Topic-based Social Influence Analysis for the Wimbledon Championships
Efficient identification of Web communities
LinkSAGE: Optimizing Job Matching Using Graph Neural Networks
Soft-CsGDT: soft cost-sensitive Gaussian decision tree for cost-sensitive classification of data streams
QGRL: Quaternion Graph Representation Learning for Heterogeneous Feature Data Clustering
Online Preference Weight Estimation Algorithm with Vanishing Regret for Car-Hailing in Road Network
Healthcare Data Mining with Matrix Models
Medical Mining: KDD 2015 Tutorial
MapExplorer: New Content Generation from Low-Dimensional Visualizations
Revisiting Personalized Federated Learning: Robustness Against Backdoor Attacks
Recognizing Unseen Objects via Multimodal Intensive Knowledge Graph Propagation
Should You Trust Your Money to a Robot?
Revisiting Neural Retrieval on Accelerators
Systematic data selection to mine concept-drifting data streams
Heterogeneous data fusion for alzheimer's disease study
Games for games: manipulating contexts in human computation games
Butterfly Counting in Bipartite Networks
Correlation clustering in MapReduce
Assessing data mining results via swap randomization
Fast Text Generation with Text-Editing Models
Mathematical Notions vs. Human Perception of Fairness: A Descriptive Approach to Fairness for Machine Learning
Learning time-series shapelets
Efficient and Joint Hyperparameter and Architecture Search for Collaborative Filtering
Profiling Deep Learning Workloads at Scale using Amazon SageMaker
Modeling delayed feedback in display advertising
Clockwork: A Delay-Based Global Scheduling Framework for More Consistent Landing Times in the Data Warehouse
Palette power: enabling visual search through colors
Preventing Strategic Behaviors in Collaborative Inference for Vertical Federated Learning
Web Personalization and Recommender Systems
Automated Selection of Rule Induction Methods Based on Recursive Iteration of Resampling Methods and Multiple Statistical Testing
All Models Are Useful: Bayesian Ensembling for Robust High Resolution COVID-19 Forecasting
Safe and efficient screening for sparse support vector machine
Proceedings of the Eighth ACM SIGKDD International Conference on Knowledge Discovery and Data Mining, July 23-26, 2002, Edmonton, Alberta, Canada
NeuroCut: A Neural Approach for Robust Graph Partitioning
Email data cleaning
SepDiff: Self-Encoding Parameter Diffusion for Learning Latent Semantics
Cuckoo Linear Algebra
Multi-Round Influence Maximization
Scaling Training Data with Lossy Image Compression
The Next Decade of Data Science
Scalable Exploratory Data Mining of Distributed Geoscientific Data
Construction of Directed 2K Graphs
Label Noise Reduction in Entity Typing by Heterogeneous Partial-Label Embedding
Deep Reinforcement Learning with Applications in Transportation
Towards Unified Conversational Recommender Systems via Knowledge-Enhanced Prompt Learning
IMMC: incremental maximum margin criterion
Improved testing of low rank matrices
Where are we in embedding spaces?
Adapting Large Vision-Language Models to Visually-Aware Conversational Recommendation
Hypformer: Exploring Efficient Transformer Fully in Hyperbolic Space
High-Dimensional Similarity Search with Quantum-Assisted Variational Autoencoder
A Computer-aided Visual Exploration System for Knowledge Discovery from Images
Enabling analysts in managed services for CRM analytics
Stable Learning via Differentiated Variable Decorrelation
CrossLinear: Plug-and-Play Cross-Correlation Embedding for Time Series Forecasting with Exogenous Variables
LaTCoder: Converting Webpage Design to Code with Layout-as-Thought
Mind the gaps: weighting the unknown in large-scale one-class collaborative filtering
Efficient Algorithms for Relevant Quantities of Friedkin-Johnsen Opinion Dynamics Model
Mining IC test data to optimize VLSI testing
Triplet Attention: Rethinking the Similarity in Transformers
Exploration in Online Advertising Systems with Deep Uncertainty-Aware Learning
Deep Learning based Crop Row Detection with Online Domain Adaptation
Automatic Feature Mining for Personalized Digital Image Retrieval
AdSEE: Investigating the Impact of Image Style Editing on Advertisement Attractiveness
Semi-supervised Drifted Stream Learning with Short Lookback
A system for automated mapping of bill-of-materials part numbers
Improving predictions using aggregate information
Toward Real-life Dialogue State Tracking Involving Negative Feedback Utterances
The bang for the buck: fair competitive viral marketing from the host perspective
Proceedings of the Second International Conference on Knowledge Discovery and Data Mining (KDD-96), Portland, Oregon, USA
Online Adaptive Asymmetric Active Learning for Budgeted Imbalanced Data
GuARD: Effective Anomaly Detection through a Text-Rich and Graph-Informed Language Model
Interpretable Deep Graph Generation with Node-edge Co-disentanglement
Covering Cracks in Content Moderation: Delexicalized Distant Supervision for Illicit Drug Jargon Detection
Selecting a characteristic set of reviews
Web site mining: a new way to spot competitors, customers and suppliers in the world wide web
GAL-VNE: Solving the VNE Problem with Global Reinforcement Learning and Local One-Shot Neural Prediction
Graph Representation Learning via Hard and Channel-Wise Attention Networks
Extracting Domain Semantics for Knowledge Discovery in Relational Databases
Detecting changes in large data sets of payment card data: a case study
IntelliLight: A Reinforcement Learning Approach for Intelligent Traffic Light Control
Studying blog features over link popularity
Direct optimization of ranking measures for learning to rank models
Buying or Browsing?: Predicting Real-time Purchasing Intent using Attention-based Deep Network with Multiple Behavior
Big Data with ADAMS
Fast locality-sensitive hashing
Conversion Prediction Using Multi-task Conditional Attention Networks to Support the Creation of Effective Ad Creatives
Scale Calibration of Deep Ranking Models
Taming the Domain Shift in Multi-source Learning for Energy Disaggregation
Detecting outliers on arbitrary data streams using anytime approaches
Collective, Hierarchical Clustering from Distributed, Heterogeneous Data
Bridging Textual-Collaborative Gap through Semantic Codes for Sequential Recommendation
Is a Single Vector Enough?: Exploring Node Polysemy for Network Embedding
Generalized Score Functions for Causal Discovery
Product selection problem: improve market share by learning consumer behavior
Discovering evolutionary theme patterns from text: an exploration of temporal text mining
Adaptive Model Pooling for Online Deep Anomaly Detection from a Complex Evolving Data Stream
Visual analysis of documents with semantic graphs
MethaneS2CM: A Dataset for Multispectral Deep Methane Emission Detection
FedAPEN: Personalized Cross-silo Federated Learning with Adaptability to Statistical Heterogeneity
Category detection using hierarchical mean shift
Information cascade at group scale
People, Computers, and The Hot Mess of Real Data
Temporal Prototype-Aware Learning for Active Voltage Control on Power Distribution Networks
Discovering frequent patterns in sensitive data
Fragile Earth: AI for Climate Mitigation, Adaptation, and Environmental Justice
Seeing the Unseen: Learning Basis Confounder Representations for Robust Traffic Prediction
Temporal Graph Signal Decomposition
Variational Inference for Training Graph Neural Networks in Low-Data Regime through Joint Structure-Label Estimation
Towards Fair Federated Learning
Learning Strong Graph Neural Networks with Weak Information
Taming Recommendation Bias with Causal Intervention on Evolving Personal Popularity
Pre-Training with Transferable Attention for Addressing Market Shifts in Cross-Market Sequential Recommendation
Evaluating Conversational Recommender Systems via User Simulation
Contrastive Cross-domain Recommendation in Matching
Urban point-of-interest recommendation by mining user check-in behaviors
Incorporating Retrieval-based Causal Learning with Information Bottlenecks for Interpretable Molecular Graph Learning
Shapley Counterfactual Credits for Multi-Agent Reinforcement Learning
Learning Elastic Embeddings for Customizing On-Device Recommenders
Streaming Hierarchical Clustering Based on Point-Set Kernel
On mining cross-graph quasi-cliques
Bounded coordinate-descent for biological sequence classification in high dimensional predictor space
Personalized Prefix Embedding for POI Auto-Completion in the Search Engine of Baidu Maps
Anonymizing transaction databases for publication
Gemello: Creating a Detailed Energy Breakdown from Just the Monthly Electricity Bill
Analysis and Applications of Class-wise Robustness in Adversarial Training
Learning Sparse Models at Scale
1-dimensional splines as building blocks for improving accuracy of risk outcomes models
Mitigating Redundancy in Deep Recommender Systems: A Field Importance Distribution Perspective
A Survey of Large Language Models for Graphs
CBLab: Supporting the Training of Large-scale Traffic Control Policies with Scalable Traffic Simulation
Common component analysis for multiple covariance matrices
Novel geospatial interpolation analytics for general meteorological measurements
Reinforcing Pretrained Models for Generating Attractive Text Advertisements
Data mining to predict and prevent errors in health insurance claims processing
Handling Information Loss of Graph Neural Networks for Session-based Recommendation
Enhancing Homophily-Heterophily Separation: Relation-Aware Learning in Heterogeneous Graphs