yusuke1997/dblp-id-title huggingface dataset:
Aggregation-based feature invention and relational concept classes
Human-Centered Clustering for Time Series Data
Weight-Constrained Simple Path Enumeration in Weighted Graph
Distributed cooperative mining for information consortia
From Variability to Stability: Advancing RecSys Benchmarking Practices
The Co-Evolution Model for Social Network Evolving and Opinion Migration
SNARE: a link analytic system for graph labeling and risk detection
Application of neural networks to biological data mining: a case study in protein sequence classification
An Auto-Coupon Framework for Advertiser Retention in Online Advertising
Scalable text and link analysis with mixed-topic link models
Efficient SimRank computation via linearizationPublication of this article pending inquiry
Functional Zone Based Hierarchical Demand Prediction For Bike System Expansion
SigniTrend: scalable detection of emerging topics in textual streams by hashed significance thresholds
Discovering highly reliable subgraphs in uncertain graphs
HyperLogLog Hyperextended: Sketches for Concave Sublinear Frequency Statistics
Subsampling for efficient and effective unsupervised outlier detection ensembles
Rubik: Knowledge Guided Tensor Factorization and Completion for Health Data Analytics
Regional-Local Adversarially Learned One-Class Classifier Anomalous Sound Detection in Global Long-Term Space
FoRAGe: High-CTR Food Image Synthesis with Retrieval-Augmented Diffusion Model
Repetition-aware content placement in navigational networks
AutoNE: Hyperparameter Optimization for Massive Network Embedding
Revisiting Random Binning Features: Fast Convergence and Strong Parallelizability
BART for Knowledge Grounded Conversations
Towards efficient mining of proportional fault-tolerant frequent itemsets
Know Your Needs Better: Towards Structured Understanding of Marketer Demands with Analogical Reasoning Augmented LLMs
The Generalized Mean Densest Subgraph Problem
Mining hepatitis data with temporal abstraction
Difference-in-Differences Subset Scan
Real Time Index and Search Across Large Quantities of GNN Experts for Low Latency Online Learning
Modelling political disaffection from Twitter data
Identifying Coordinated Accounts on Social Media through Hidden Influence and Group Behaviours
Certified Robustness on Visual Graph Matching via Searching Optimal Smoothing Range
Online Item Cold-Start Recommendation with Popularity-Aware Meta-Learning
TINET: Learning Invariant Networks via Knowledge Transfer
Graph Structural Attack by Perturbing Spectral Distance
InLN: Knowledge-aware Incremental Leveling Network for Dynamic Advertising
An event-based framework for characterizing the evolutionary behavior of interaction graphs
Data winnowing
A general probabilistic framework for clustering individuals and objects
The Battlefront of Combating Misinformation and Coping with Media Bias
AdaGMLP: AdaBoosting GNN-to-MLP Knowledge Distillation
MAPLE: Semi-Supervised Learning with Multi-Alignment and Pseudo-Learning
Data security and integrity: developments and directions
Mining top-K high utility itemsets
Estimating business targets
Generalization Methods in Bioinformatics
Multi-scale Physics-informed Transformer With Spatio-temporal Feature Adapter For Extreme Precipitation Nowcasting
Partial Label Learning with Discrimination Augmentation
Positive-Unlabeled Learning in Streaming Networks
Balanced Order Batching with Task-Oriented Graph Clustering
Identification of structurally important amino acids in proteins by graph-theoretic measures
Efficient computation of PCA with SVD in SQL
Active learning using adaptive resampling
Magnet community identification on social networks
Deep Choice Model Using Pointer Networks for Airline Itinerary Prediction
Learning to Simulate Human Mobility
The PanQ Tool and EMF SQL for Complex Data Management
ConSTGAT: Contextual Spatial-Temporal Graph Attention Network for Travel Time Estimation at Baidu Maps
Feature-Induced Manifold Disambiguation for Multi-View Partial Multi-label Learning
Subjective Interpretation of Complex Data: Requirements for Supporting Kansei Mining Process
Offline Evaluation of Ranking Policies with Click Models
Mining Reliable Information from Passively and Actively Crowdsourced Data
Playlist prediction via metric embedding
Multi-Aspect Streaming Tensor Completion
China's national personal credit scoring system: a real-life intelligent knowledge application
FreRA: A Frequency-Refined Augmentation for Contrastive Learning on Time Series Classification
SMOILE: A Shopper Marketing Optimization and Inverse Learning Engine
TCS: efficient topic discovery over crowd-oriented service data
State-Driven Dynamic Sensor Selection and Prediction with State-Stacked Sparseness
Automating exploratory data analysis for efficient data mining
APEX 2 : Adaptive and Extreme Summarization for Personalized Knowledge Graphs
FleetRec: Large-Scale Recommendation Inference on Hybrid GPU-FPGA Clusters
Applying a Data Miner To Heterogeneous Schema Integration
DipDNN: Preserving Inverse Consistency and Approximation Efficiency for Invertible Learning
Fair Allocation Over Time, with Applications to Content Moderation
Data for Good: Abstract
Learning a complex metabolomic dataset using random forests and support vector machines
Frequent term-based text clustering
Approximation Algorithms for Size-Constrained Non-Monotone Submodular Maximization in Deterministic Linear Time
SPARTan: Scalable PARAFAC2 for Large & Sparse Data
SmartDispatch: enabling efficient ticket dispatch in an IT service environment
How to Calibrate your Neural Network Classifier: Getting True Probabilities from a Classification Model
Sufficient Vision Transformer
FUNNEL: automatic mining of spatially coevolving epidemics
Parallel Branch-and-Bound Graph Search for Correlated Association Rules
Mining Unstructured Data
Re-identification Attack to Privacy-Preserving Data Analysis with Noisy Sample-Mean
Automatic Generation of Product-Image Sequence in E-commerce
Climate Downscaling Using YNet: A Deep Convolutional Network with Skip Connections and Fusion
On the separability of structural classes of communities
Data Science for the Real Estate Industry
Proceedings of the 12th International Workshop on Data Mining in Bioinformatics, BIOKDD 2013, Chicago, IL, USA, August 11, 2013
Algorithm for low-variance biclusters to identify coregulation modules in sequencing datasets
Batch discovery of recurring rare classes toward identifying anomalous samples
Very sparse random projections
Causal-aware Graph Neural Architecture Search under Distribution Shifts
Subjective Interpretation Of Complex Data: Requirements For Supporting Kansei Mining Process
A system for extracting top-K lists from the web
Characterizing and Detecting Malicious Accounts in Privacy-Centric Mobile Social Networks: A Case Study
Online learning to diversify from implicit feedback
The information diffusion model in the blog world
Learning Classifiers under Delayed Feedback with a Time Window Assumption
Customer targeting models using actively-selected web content
Relay-Linking Models for Prominence and Obsolescence in Evolving Networks
Your Graph Recommenders are Provably Doing Graph Contrastive Learning
FDML: A Collaborative Machine Learning Framework for Distributed Features
Information distance from a question to an answer
Catch Me If You Can: Detecting Pickpocket Suspects from Large-Scale Transit Records
Probabilistic Graphical Models of Dyslexia
DeepProbe: Information Directed Sequence Understanding and Chatbot Design via Recurrent Neural Networks
Understanding urban human activity and mobility patterns using large-scale location-based data from online social media
Contextual Self-attentive Temporal Point Process for Physical Decommissioning Prediction of Cloud Assets
Extreme Multi-Label Classification for Ad Targeting using Factorization Machines
Modeling urban traffic dynamics in coexistence with urban data streams
Towards Conversational Recommender Systems
The practitioner's viewpoint to data mining: key lessons learned in the trenches and case studies
Convex Factorization Machine for Toxicogenomics Prediction
Spatio-Temporal Trajectory Similarity Learning in Road Networks
The Impact of Site Structure and User Environment on Session Reconstruction in Web Usage Analysis
Distributed Multi-Task Relationship Learning
Logical Reasoning with Relation Network for Inductive Knowledge Graph Completion
Language Scaling: Applications, Challenges and Approaches
New Robust Metric Learning Model Using Maximum Correntropy Criterion
Separating Graph Generative Models via Degree Distributions
The Second Workshop on Applied Machine Learning Management
Towards Context-Aware Traffic Classification via Time-Wavelet Fusion Network
BLOCKSET (Block-Aligned Serialized Trees): Reducing Inference Latency for Tree ensemble Deployment
CAMEF: Causal-Augmented Multi-Modality Event-Driven Financial Forecasting by Integrating Time Series Patterns and Salient Macroeconomic Announcements
Federated Adversarial Debiasing for Fair and Transferable Representations
RecMax: exploiting recommender systems for fun and profit
Jointly modeling aspects, ratings and sentiments for movie recommendation (JMARS)
S2RL: Do We Really Need to Perceive All States in Deep Multi-Agent Reinforcement Learning?
Mining adaptively frequent closed unlabeled rooted trees in data streams
Scalable look-ahead linear regression trees
Mining social networks for personalized email prioritization
Capacity and Complexity Control in Predicting the Spread Between Borrowing and Lending Interest Rates
Differentially Private Recommender Systems: Building Privacy into the Netflix Prize Contenders
Regularized Regression for Hierarchical Forecasting Without Unbiasedness Conditions
Advances in Recommender Systems: From Multi-stakeholder Marketplaces to Automated RecSys
Exploitation and exploration in a performance based contextual advertising system
BDT: Gradient Boosted Decision Tables for High Accuracy and Scoring Efficiency
Large scale visual recommendations from street fashion images
Distributed Hybrid CPU and GPU training for Graph Neural Networks on Billion-Scale Heterogeneous Graphs
ArnoldiGCL: Graph Contrastive Learning via Learnable Arnoldi-Based Guided Spectral Chebyshev Polynomial Filters
Trustworthy Transfer Learning: Transferability and Trustworthiness
Tackling Federated Long-Tailed Learning via Synthetic Feature-Based Decoupled Training
An Interpretable, Flexible, and Interactive Probabilistic Framework for Melody Generation
Detecting research topics via the correlation between graphs and texts
Mining for Causes of Cancer: Machine Learning Experiments at Various Levels of Detail
When Box Meets Graph Neural Network in Tag-aware Recommendation
PAC-Wrap: Semi-Supervised PAC Anomaly Detection
Exploring social tagging graph for web object classification
Angle-based outlier detection in high-dimensional data
TH-Bench: Evaluating Evading Attacks via Humanizing AI Text on Machine-Generated Text Detectors
Non-Homophilic Graph Pre-Training and Prompt Learning
Building a Better Self-Driving Car: Hardware, Software, and Knowledge
Scale-out beyond map-reduce
The Evolving Meaning of Information Security
Data Mining and Model Simplicity: A Case Study in Diagnosis
Fast mining and forecasting of complex time-stamped events
Contextual Fact Ranking and Its Applications in Table Synthesis and Compression
Small is beautiful: discovering the minimal set of unexpected patterns
Policy-Based Bayesian Active Causal Discovery with Deep Reinforcement Learning
Investigating Trojan Attacks on Pre-trained Language Model-powered Database Middleware
Proceedings of the 3nd ACM SIGKDD Workshop on Data Mining in Bioinformatics (BIOKDD 2003), August 27th, 2003, Washington, DC, USA
Beyond Concise and Colorful: Learning Intelligible Rules
Pragmatic text mining: minimizing human effort to quantify many issues in call logs
Parallel mining of closed sequential patterns
Learning to Assign: Towards Fair Task Assignment in Large-Scale Ride Hailing
TransPlace: Transferable Circuit Global Placement via Graph Neural Network
Efficient Parallel Algorithms for Mining Associations
FlexGNN: A High-Performance, Large-Scale Full-Graph GNN System with Best-Effort Training Plan Optimization
PECOS: Prediction for Enormous and Correlated Output Spaces
Physics-Guided Learning of Meteorological Dynamics for Weather Downscaling and Forecasting
Orthogonality Matters: Invariant Time Series Representation for Out-of-distribution Classification
Data mining techniques for optimizing inventories for electronic commerce
UA-FedRec: Untargeted Attack on Federated News Recommendation
Relational Markov models and their application to adaptive web navigation
Large-Scale Machine Learning at Verizon: Theory and Applications
Rank-directed layout of UML class diagrams
Natural communities in large linked networks
Data mining for outliers with robust statistics
Mining discriminative components with low-rank and sparsity constraints for face recognition
A Bayesian network classifier with inverse tree structure for voxelwise magnetic resonance image analysis
Sample Adaptive Multiple Kernel Learning for Failure Prediction of Railway Points
Self-Regularization with Sparse Autoencoders for Controllable LLM-based Classification
Graph Structural-topic Neural Network
Cost-Efficient Fraud Risk Optimization with Submodularity in Insurance Claim
Adversarial Substructured Representation Learning for Mobile User Profiling
Large Scale Data Mining: Challenges and Responses
Pruning and Summarizing the Discovered Associations
Scalable supervised dimensionality reduction using clustering
Management and analytic of biomedical big data with cloud-based in-memory database and dynamic querying: a hands-on experience with real-world data
AsySQN: Faster Vertical Federated Learning Algorithms with Better Computation Resource Utilization
Continuous Experience-aware Language Model
Rapid Regression Detection in Software Deployments through Sequential Testing
LWI-SVD: low-rank, windowed, incremental singular value decompositions on time-evolving data sets
Very sparse stable random projections for dimension reduction in l alpha (0 <alpha<=2) norm
Quantizing Text-attributed Graphs for Semantic-Structural Integration
Repeat Buyer Prediction for E-Commerce
Ads Recommendation in a Collapsed and Entangled World
Knowledge discovery from massive healthcare claims data
Nonparametric Mixture of Sparse Regressions on Spatio-Temporal Data - An Application to Climate Prediction
M5: Multi-Modal Multi-Interest Multi-Scenario Matching for Over-the-Top Recommendation
Universal multi-dimensional scaling
COM: a generative model for group recommendation
Improving Multi-modal Recommender Systems by Denoising and Aligning Multi-modal Content and User Feedback
Detecting Early Indicator Cars in an Automotive Database: A Multi-Strategy Approach
Time series shapelets: a new primitive for data mining
MockLLM: A Multi-Agent Behavior Collaboration Framework for Online Job Seeking and Recruiting
Discovering Enrollment Knowledge in University Databases
Growing Simpler Decision Trees to Facilitate Knowledge Discovery
Quantifying trends accurately despite classifier error and class imbalance
InvDiff: Invariant Guidance for Bias Mitigation in Diffusion Models
Accessible Online Meetings and Presentations
Spatial Hierarchical Meta-Learning for Single-Point Map Matching
Global distance-based segmentation of trajectories
Inferring User Social Class in Online Social Networks
A Review of Modern Recommender Systems Using Generative Models (Gen-RecSys)
JAM: Java Agents for Meta-Learning over Distributed Databases
Stealing Training Graphs from Graph Neural Networks
Towards Building an Intelligent Chatbot for Customer Service: Learning to Respond at the Appropriate Time
A new collaborative filtering approach for increasing the aggregate diversity of recommender systems
Input Snapshots Fusion for Scalable Discrete-Time Dynamic Graph Neural Networks
Anatomy of a Privacy-Safe Large-Scale Information Extraction System Over Email
Charting Pathways to AI-Enabled Healthcare
Large-scale graph mining using backbone refinement classes
Weighted Association Rule Mining using weighted support and significance framework
A time-dependent enhanced support vector machine for time series regression
Software as a Medical Device: Regulating AI in Healthcare via Responsible AI
Measure Domain's Gap: A Similar Domain Selection Principle for Multi-Domain Recommendation
Multimodal Emergent Fake News Detection via Meta Neural Process Networks
BatchRank: A Novel Batch Mode Active Learning Framework for Hierarchical Classification
BatteryLife: A Comprehensive Dataset and Benchmark for Battery Life Prediction
Increasing the Efficiency of Data Mining Algorithms with Breadth-First Marker Propagation
Multi-Temporal Relationship Inference in Urban Areas
Evaluation and Benchmarking of LLM Agents: A Survey
Contrastive Learning for Inventory Add Prediction at Fliggy
Representation Learning of Temporal Graphs with Structural Roles
Towards Variance Reduction for Reinforcement Learning of Industrial Decision-making Tasks: A Bi-Critic based Demand-Constraint Decoupling Approach
Domain-Driven LLM Development: Insights into RAG and Fine-Tuning Practices
Z-Miner: An Efficient Method for Mining Frequent Arrangements of Event Intervals
Challenges in mining social network data: processes, privacy, and paradoxes
UD-GNN: Uncertainty-aware Debiased Training on Semi-Homophilous Graphs
ASPIRE: Air Shipping Recommendation for E-commerce Products via Causal Inference Framework
Temporal pattern discovery for trends and transient effects: its application to patient records
Dynamic Pricing for Multi-Retailer Delivery Platforms with Additive Deep Learning and Evolutionary Optimization
How optimized environmental sensing helps address information overload on the web
Marionette: Fine-Grained Conditional Generative Modeling of Spatiotemporal Human Trajectory Data Beyond Imitation
Unsupervised Generative Feature Transformation via Graph Contrastive Pre-training and Multi-objective Fine-tuning
Using co-visitation networks for detecting large scale online display advertising exchange fraud
Are Your Fairness Metrics Accurate? A Semi-Supervised Approach to Improving Fairness Estimates Under Sample Selection Bias
Self-Tuning Self-Supervised Image Anomaly Detection
Forward Once for All: Structural Parameterized Adaptation for Efficient Cloud-coordinated On-device Recommendation
Bias Detection via Maximum Subgroup Discrepancy
Personal privacy vs population privacy: learning to attack anonymization
CatchSync: catching synchronized behavior in large directed graphs
A bag of paths model for measuring structural similarity in Web documents
Attribute-Enhanced Similarity Ranking for Sparse Link Prediction
Advances in Human Event Modeling: From Graph Neural Networks to Language Models
FLASH: Fast Bayesian Optimization for Data Analytic Pipelines
Broad scale predictive modeling and marketing optimization in retail sales
Integrating System State into Spatio Temporal Graph Neural Network for Microservice Workload Prediction
PPDsparse: A Parallel Primal-Dual Sparse Method for Extreme Classification
DeepWalk: online learning of social representations
Learnable-Differentiable Finite Volume Solver for Accelerated Simulation of Flows
On socio-spatial group query for location-based social networks
Discovering Informative Patterns and Data Cleaning
Faster and Generalized Temporal Triangle Counting, via Degeneracy Ordering
STAR: A General Architecture for the Support of Distortion Oriented Displays
Active Opinion Maximization in Social Networks
A Dynamic Pipeline for Spatio-Temporal Fire Risk Prediction
Diversity in ranking via resistive graph centers
Probabilistic author-topic models for information discovery
xGAIL: Explainable Generative Adversarial Imitation Learning for Explainable Human Decision Analysis
GraphStorm an Easy-to-use and Scalable Graph Neural Network Framework: From Beginners to Heroes
Bid optimizing and inventory scoring in targeted online advertising
Bi-Objective Contract Allocation for Guaranteed Delivery Advertising
Optimizing time series discretization for knowledge discovery
Learning the Covariance of Treatment Effects Across Many Weak Experiments
Graph2Route: A Dynamic Spatial-Temporal Graph Neural Network for Pick-up and Delivery Route Prediction
Geometer: Graph Few-Shot Class-Incremental Learning via Prototype Representation
The minimum consistent subset cover problem and its applications in data mining
PrePeP: A Tool for the Identification and Characterization of Pan Assay Interference Compounds
Applying Link-Based Classification to Label Blogs
Query result clustering for object-level search
Classification of genes using probabilistic models of microarray expression profiles
Funnel report mining for the MSN network
Addressing Correlated Latent Exogenous Variables in Debiased Recommender Systems
A Hands-on Tutorial on Time Series Imputation with ImputeGAP
The Wisdom of Crowds: Best Practices for Data Prep & Machine Learning Derived from Millions of Data Science Workflows
Friendship and mobility: user movement in location-based social networks
Machine Learning Robustness, Fairness, and their Convergence
Routing Evidence for Unseen Actions in Video Moment Retrieval
Learning to Predict Rare Events in Event Sequences
Toward Automated Fact-Checking: Detecting Check-worthy Factual Claims by ClaimBuster
Longitudinal LASSO: Jointly Learning Features and Temporal Contingency for Outcome Prediction
Web Scale Graph Mining for Cyber Threat Intelligence
Adaptive Web Usage Profiling
Proceedings of the International Workshop on Multimedia Data Mining, MDM/KDD'2000, August 20th, 2000, Boston, MA, USA
Display advertising impact: search lift and social influence
AdKDD 2023
IRNet: A General Purpose Deep Residual Regression Framework for Materials Discovery
PolyFormer: Scalable Node-wise Filters via Polynomial Graph Transformer
AiAds: Automated and Intelligent Advertising System for Sponsored Search
GrokNet: Unified Computer Vision Model Trunk and Embeddings For Commerce
Discovery net: towards a grid of knowledge discovery
Mission-Based Navigational Behaviour Modeling for Web Recommender Systems
Beyond Point Prediction: Capturing Zero-Inflated & Heavy-Tailed Spatiotemporal Data with Deep Extreme Mixture Models
Visualization support for a user-centered KDD process
Temporal Dynamics-Aware Adversarial Attacks on Discrete-Time Dynamic Graph Models
Feature Extraction for Massive Data Mining
Using Machine Learning to Assess the Risk of and Prevent Water Main Breaks
Thriving as a data miner in the real world
Shilling Black-box Review-based Recommender Systems through Fake Review Generation
Deep Graph Learning: Foundations, Advances and Applications
Learning OOD Robust Neural Operator with Risk-Averse Stochastic Optimization
Grounding Visual Concepts for Zero-Shot Event Detection and Event Captioning
Extracting shared subspace for multi-label classification
Integrating Classification and Association Rule Mining
A Multiresolution Approach to Recommender Systems
Learning to Prescribe Interventions for Tuberculosis Patients Using Digital Adherence Data
PMKLC: Parallel Multi-Knowledge Learning-based Lossless Compression for Large-Scale Genomics Database
Scalable all-pairs similarity search in metric spaces
Infinite Ensemble for Image Clustering
Online controlled experiments at large scale
Hierarchical Proxy Modeling for Improved HPO in Time Series Forecasting
Learning Models of Individual Behavior in Chess
TimeGraph: Synthetic Benchmark Datasets for Robust Time-Series Causal Discovery
Fast logistic regression for text categorization with variable-length n-grams
Automatically Discovering User Consumption Intents in Meituan
Mining Interesting Knowledge Using DM-II
Combining incremental Hidden Markov Model and Adaboost algorithm for anomaly intrusion detection
DOULION: counting triangles in massive graphs with a coin
Producer-Side Experiments Based on Counterfactual Interleaving Designs for Online Recommender Systems
Unbiased Locally Private Estimator for Polynomials of Laplacian Variables
Embedding Compression with Hashing for Efficient Representation Learning in Large-Scale Graph
Generalizing the notion of support
Tracking multiple topics for finding interesting articles
Error Bounds for the Network Scale-Up Method