yusuke1997/dblp-id-title huggingface dataset:
Emerging Trends in Personality Identification Using Online Social Networks - A Literature Survey
A Unified Framework with Multi-source Data for Predicting Passenger Demands of Ride Services
Trustworthiness-Driven Graph Convolutional Networks for Signed Network Embedding
X-FSPMiner: A Novel Algorithm for Frequent Similar Pattern Mining
Mining Repetitive Negative Sequential Patterns with Gap Constraints
SOHUPDS+: An Efficient One-phase Algorithm for Mining High Utility Patterns over a Data Stream
Mining Product Adopter Information from Online Reviews for Improving Product Recommendation
Multi-Task Learning with Sequential Dependence Toward Industrial Applications: A Systematic Formulation
An Efficient Framework for Epidemiological Parameter Estimation via Graph Reduction and Graph Neural Networks
Neural Serendipity Recommendation: Exploring the Balance between Accuracy and Novelty with Sparse Explicit Feedback
Enhancing Unsupervised Outlier Model Selection: A Study on IREOS Algorithms
Ranking Metric Anomaly in Invariant Networks
Self-supervision for Tabular Data by Learning to Predict Additive Homoskedastic Gaussian Noise as Pretext
Forecasting Graph-Based Time-Dependent Data with Graph Sequence Attention
A Novel Classification Technique based on Formal Methods
A Unified Multi-view Clustering Algorithm Using Multi-objective Optimization Coupled with Generative Model
Adaptive Model Rules From High-Speed Data Streams
Networked Time-series Prediction with Incomplete Data via Generative Adversarial Network
Neural-Symbolic Methods for Knowledge Graph Reasoning: A Survey
Distributional Learning for Network Alignment with Global Constraints
Ranking from Crowdsourced Pairwise Comparisons via Smoothed Riemannian Optimization
Feature Selection via Transferring Knowledge Across Different Classes
Solving inverse frequent itemset mining with infrequency constraints via large-scale linear programs
A Stochastic Algorithm Based on Reverse Sampling Technique to Fight Against the Cyberbullying
Recommending Users and Communities in Social Media
MP 2 SDA: Multi-Party Parallelized Sparse Discriminant Learning
Multi-Concept Representation Learning for Knowledge Graph Completion
Towards an Optimal Outdoor Advertising Placement: When a Budget Constraint Meets Moving Trajectories
Learning Sentence-to-Hashtags Semantic Mapping for Hashtag Recommendation on Microblogs
Computing top- k Closeness Centrality Faster in Unweighted Graphs
Accuracy, Fairness, Diversity All at Once: An Influence-Function-Guided Data Enhancement Approach for Recommender System
MoMENt: Marked Point Processes with Memory-Enhanced Neural Networks for User Activity Modeling
Knowledge Transfer with Weighted Adversarial Network for Cold-Start Store Site Recommendation
Function-on-Function Regression with Mode-Sparsity Regularization
Consensus Guided Multi-View Clustering
Dynamic Environment Responsive Online Meta-Learning with Fairness Awareness
Towards Domain-Aware Stable Meta Learning for Out-of-Distribution Generalization
A Method for Mining Granger Causality Relationship on Atmospheric Visibility
Towards Faster Deep Graph Clustering via Efficient Graph Auto-Encoder
Modeling Temporal Patterns with Dilated Convolutions for Time-Series Forecasting
Incremental Community Detection on Large Complex Attributed Network
Subclass-wise Logit Perturbation for Multi-label Learning
Context-Aware Recommendation Using Role-Based Trust Network
Means of Hitting Times for Random Walks on Graphs: Connections, Computation, and Optimization
Predicting and Identifying Missing Node Information in Social Networks
High-Value Token-Blocking: Efficient Blocking Method for Record Linkage
Discovering Time-aware Hidden Dependencies with Personalized Graphical Structure in Electronic Health Records
LSTGCN: Inductive Spatial Temporal Imputation Using Long Short-Term Dependencies
Dual-MGAN: An Efficient Approach for Semi-supervised Outlier Detection with Few Identified Anomalies
Intelligent Data Analysis using Optimized Support Vector Machine Based Data Mining Approach for Tourism Industry
Diverse Structure-Aware Relation Representation in Cross-Lingual Entity Alignment
Integrating Group Consensus for Competitive Influence Maximization in OSNs
Attacking Shortest Paths by Cutting Edges
Hierarchical Bayesian Inference and Recursive Regularization for Large-Scale Classification
Communities in Streaming Graphs: Small Space Data Structure, Benchmark Data Generation, and Linear Algorithm
New Algorithms of Feature Selection and Big Data Assignment for CBR System Integrated by Bayesian Network
Privacy-Preserving Machine Learning Based on Cryptography: A Survey
High-Order Structure Exploration on Massive Graphs: A Local Graph Clustering Perspective
Adaptive Cluster Tendency Visualization and Anomaly Detection for Streaming Data
Learning to detect events with Markov-modulated poisson processes
Inferring Dynamic Diffusion Networks in Online Media
A Self-Representation Method with Local Similarity Preserving for Fast Multi-View Outlier Detection
Streaming Data Preprocessing via Online Tensor Recovery for Large Environmental Sensor Networks
Scale-Aware Neural Architecture Search for Multivariate Time Series Forecasting
Time-Aware Graph Embedding: A Temporal Smoothness and Task-Oriented Approach
Multi-view Graph Representation Learning Beyond Homophily
Partial Multi-Label Learning via Exploiting Instance and Label Correlations
A Model-Agnostic Framework for Fast Spatial Anomaly Detection
Causal Meta-learning with Multi-view Graphs for Cold-start Recommendation
Learning with Asynchronous Labels
Real-Time Estimation of the Urban Air Quality with Mobile Sensor System
Improving Bandit Learning Via Heterogeneous Information Networks: Algorithms and Applications
S2OSC: A Holistic Semi-Supervised Approach for Open Set Classification
Who will Win the Data Science Competition? Insights from KDD Cup 2019 and Beyond
GGATB-LSTM: Grouping and Global Attention-based Time-aware Bidirectional LSTM Medical Treatment Behavior Prediction
"A 6 or a 9?": Ensemble Learning through the Multiplicity of Performant Models and Explanations
Toward Understanding and Evaluating Structural Node Embeddings
Community-Based Influence Maximization Using Network Embedding in Dynamic Heterogeneous Social Networks
Same or Different? Diff-Vectors for Authorship Analysis
DexDeepFM: Ensemble Diversity Enhanced Extreme Deep Factorization Machine Model
Translations Diversification for Expert Finding: A Novel Clustering-based Approach
Three-way Preference Completion via Preference Graph
Variable-lag Granger Causality and Transfer Entropy for Time Series Analysis
SemRe-Rank: Improving Automatic Term Extraction by Incorporating Semantic Relatedness with Personalised PageRank
Modeling information-seeker satisfaction in community question answering
ORIC: Feature Interaction Detection through Online Random Interaction Chains for Click-Through Rate Prediction
Math Word Problem Generation via Disentangled Memory Retrieval
Coordination Event Detection and Initiator Identification in Time Series Data
Subgraph Federated Learning with Information Bottleneck Constrained Generative Learning
Rumor Blocking through Online Link Deletion on Social Networks
Online Active Learning with Expert Advice
Review of Clustering Methods for Functional Data
Graph Representation Learning Enhanced Semi-Supervised Feature Selection
Querying Discriminative and Representative Samples for Batch Mode Active Learning
Fast Discovery of Group Lag Correlations in Streams
A Novel Bipartite Graph Based Competitiveness Degree Analysis from Query Logs
Batch Mode Active Sampling Based on Marginal Probability Distribution Matching
Special issue on best of SIGKDD 2011
Moving Destination Prediction Using Sparse Dataset: A Mobility Gradient Descent Approach
Automatic Recommendation of a Distance Measure for Clustering Algorithms
Temporal Structural Preserving with Subtree Attention in Dynamic Graph Transformers
Stochastic Variational Optimization of a Hierarchical Dirichlet Process Latent Beta-Liouville Topic Model
Tree model guided candidate generation for mining frequent subtrees from XML documents
ArieL: Adversarial Graph Contrastive Learning
TOMGPT: Reliable Text-Only Training Approach for Cost-Effective Multi-modal Large Language Model
Mining Dual Networks: Models, Algorithms, and Applications
Lifecycle Modeling for Buzz Temporal Pattern Discovery
Learning Graph Neural Networks with Positive and Unlabeled Nodes
Self-sufficient itemsets: An approach to screening potentially interesting associations between items
Wealth Flow Model: Online Portfolio Selection Based on Learning Wealth Flow Matrices
Pairwised Specific Distance Learning from Physical Linkages
diGRASS: Directed Graph Spectral Sparsification via Spectrum-Preserving Symmetrization
Online Stable Streaming Feature Selection via Feature Aggregation
X-distribution: Retraceable Power-law Exponent of Complex Networks
Bregman bubble clustering: A robust framework for mining dense clusters
Lifelong Online Learning from Accumulated Knowledge
Bi-Directional Recurrent Attentional Topic Model
Discovering Communities and Anomalies in Attributed Graphs: Interactive Visual Exploration and Summarization
Dual-View Anomaly Detection in Heterogeneous Information Networks with Hierarchical Neighborhood Fusion
Triangle listing in massive networks
Hierarchical Convolutional Neural Network with Knowledge Complementation for Long-Tailed Classification
Query-Driven Learning for Predictive Analytics of Data Subspace Cardinality
G-RoI: Automatic Region-of-Interest Detection Driven by Geotagged Social Media Data
Towards Informative and Diverse Dialogue Systems Over Hierarchical Crowd Intelligence Knowledge Graph
ProgressER: Adaptive Progressive Approach to Relational Entity Resolution
DMGF-Net: An Efficient Dynamic Multi-Graph Fusion Network for Traffic Prediction
Efficient Approaches to k Representative G-Skyline Queries
Multi-task Information Bottleneck Co-clustering for Unsupervised Cross-view Human Action Categorization
Convex Sparse PCA for Unsupervised Feature Learning
Erratum: A Dual Perspective Framework of Knowledge-correlation for Cross-domain Recommendation
Graph-Based Stock Recommendation by Time-Aware Relational Attention Network
VAE*: A Novel Variational Autoencoder via Revisiting Positive and Negative Samples for Top- N Recommendation
Self-Adaptive Particle Swarm Optimization for Large-Scale Feature Selection in Classification
Lost in Transduction: Transductive Transfer Learning in Text Classification
Anomaly Detection With Kernel Preserving Embedding
TechPat: Technical Phrase Extraction for Patent Mining
Framework for Variable-Lag Motif Following Relation Inference in Time Series Using Matrix Profile Analysis
Spectral Ranking Regression
Website Owner Identification through Multi-level Contrastive Representation Learning
Random Walk Sampling in Social Networks Involving Private Nodes
Cross-Dependency Inference in Multi-Layered Networks: A Collaborative Filtering Perspective
Slack-Factor-Based Fuzzy Support Vector Machine for Class Imbalance Problems
Graph Neural Networks for Fast Node Ranking Approximation
Improving Node Classification Accuracy of GNN through Input and Output Intervention
Exploiting Defenses against GAN-Based Feature Inference Attacks in Federated Learning
Unbiased Characterization of Node Pairs over Large Graphs
Scholar2vec: Vector Representation of Scholars for Lifetime Collaborator Prediction
Non-Parallel Story Author-Style Transfer with Disentangled Representation Learning
Efficient online learning for multitask feature selection
Evaluation-free Time-series Forecasting Model Selection via Meta-learning
BISC: A bitmap itemset support counting approach for efficient frequent itemset mining
Recommending Statutes: A Portable Method Based on Neural Networks
Heterogeneous Hyperbolic Hypergraph Neural Network for Friend Recommendation in Location-based Social Networks
Discovering Anomalies by Incorporating Feedback from an Expert
Together Is Better: Knowledge-aware Model with Resume Fusion for Online Job Recommendation
Reducing Cumulative Errors of Incremental CP Decomposition in Dynamic Online Social Networks
Discovering General Prominent Streaks in Sequence Data
KRAN: Knowledge Refining Attention Network for Recommendation
Mining Career Paths from Large Resume Databases: Evidence from IT Professionals
Have Our Cake and Eat It: Augmentation Diversity and Semantic Consistency Balanced Graph Contrastive Learning
End-to-End Continual Rare-Class Recognition with Emerging Novel Subclasses
Pattern-oriented Attention Mechanism for Multivariate Time Series Forecasting
Corpus-level and Concept-based Explanations for Interpretable Document Classification
A News-Based Framework for Uncovering and Tracking City Area Profiles: Assessment in Covid-19 Setting
Real-Time Anomaly Detection in Edge Streams
Variate Associated Domain Adaptation for Unsupervised Multivariate Time Series Anomaly Detection
Learning multiple nonredundant clusterings
Laplacian Change Point Detection for Single and Multi-view Dynamic Graphs
Latent Time-Series Motifs
An Efficient Algorithm For Weak Hierarchical Lasso
Confidence Weighted Mean Reversion Strategy for Online Portfolio Selection
Self-Supervised Dynamic Graph Representation Learning via Temporal Subgraph Contrast
Local Community Detection in Multiple Private Networks
Fair Feature Selection: A Causal Perspective
Variational Graph Autoencoder with Adversarial Mutual Information Learning for Network Representation Learning
Heterogeneous-Length Text Topic Modeling for Reader-Aware Multi-Document Summarization
StructCoder: Structure-Aware Transformer for Code Generation
An Information Theory Based Method for Quantifying the Predictability of Human Mobility
Beyond Static Boundaries: Unraveling Temporal Overlapping Communities with Information Bottleneck Guidance
Density-Aware Clustering Based on Aggregated Heat Kernel and Its Transformation
Learning Shared Representations for Recommendation with Dynamic Heterogeneous Graph Convolutional Networks
A Weighted Ensemble Classification Algorithm Based on Nearest Neighbors for Multi-Label Data Stream
Detecting Process Duration Drift Using Gamma Mixture Models in a Left-Truncated and Right-Censored Environment
On the Use of Relative Validity Indices for Comparing Clustering Approaches
Synthesis of Longitudinal Human Location Sequences: Balancing Utility and Privacy
NNC-GCN: Neighbours-to-Neighbours Contrastive Graph Convolutional Network for Semi-Supervised Classification
Network Embedding on Hierarchical Community Structure Network
Isolation-Based Anomaly Detection
A Survey on Explainable Anomaly Detection
Exploring and Exploiting Data Heterogeneity in Recommendation
MSIPA: Multi-Scale Interval Pattern-Aware Network for ICU Transfer Prediction
Side Information Fusion for Recommender Systems over Heterogeneous Information Network
Dynamic Multi-View Graph Neural Networks for Citywide Traffic Inference
Entity-Based Query Recommendation for Long-Tail Queries
Explainable Integration of Social Media Background in a Dynamic Neural Recommender
Semi-analytical method for analyzing models and model selection measures based on moment analysis
Efficient and High-Quality Seeded Graph Matching: Employing Higher-order Structural Information
A Modular Machine Learning System for Flow-Level Traffic Classification in Large Networks
Tiered Sampling: An Efficient Method for Counting Sparse Motifs in Massive Graph Streams
Critique on Natural Noise in Recommender Systems
User behavior learning and transfer in composite social networks
Privacy-Preserving Mechanisms for Multi-Label Image Recognition
Multi-View Collaborative Network Embedding
Dynamic Graph Mining for Multi-weight Multi-destination Route Planning with Deadlines Constraints
Self-Supervised Transformer for Sparse and Irregularly Sampled Multivariate Clinical Time-Series
comeNgo: A Dynamic Model for Social Group Evolution
A Framework for Exploiting Local Information to Enhance Density Estimation of Data Streams
Guest Editorial for Special Issue KDD'10
SPAP: Simultaneous Demand Prediction and Planning for Electric Vehicle Chargers in a New City
Recurrent Meta-Structure for Robust Similarity Measure in Heterogeneous Information Networks
Hierarchical Dense Pattern Detection in Tensors
Question Embedding on Weighted Heterogeneous Information Network for Knowledge Tracing
Mining Linguistic Styles in Bilateral Matching: A Contrastive Learning Approach to Reciprocal Recommendation
DOLPHIN: An efficient algorithm for mining distance-based outliers in very large datasets
Partial Sum Minimization of Singular Values Representation on Grassmann Manifolds
A Survey on Causal Inference
A Spatial-Temporal Aggregated Graph Neural Network for Docked Bike-sharing Demand Forecasting
Behavioral Targeting: The Art of Scaling Up Simple Algorithms
Iterative Time Series Imputation by Maintaining Dependency Consistency
FulBM: Fast Fully Batch Maintenance for Landmark-based 3-hop Cover Labeling
Discovering Conditional Matching Rules
Knowledge-tuning Large Language Models with Structured Medical Knowledge Bases for Trustworthy Response Generation in Chinese
A shared-subspace learning framework for multi-label classification
GLAD: Group Anomaly Detection in Social Media Analysis
Diffusion Models for Tabular Data Imputation and Synthetic Data Generation
NGUARD+: An Attention-based Game Bot Detection Framework via Player Behavior Sequences
Addressing Big Data Time Series: Mining Trillions of Time Series Subsequences Under Dynamic Time Warping
Time-Warped Sparse Non-negative Factorization for Functional Data Analysis
A Clique-Querying Mining Framework for Discovering High Utility Co-Location Patterns without Generating Candidates
Explainable Artificial Intelligence-Based Competitive Factor Identification
Learning Global and Multi-granularity Local Representation with MLP for Sequential Recommendation
ProtoNAM: Prototypical Neural Additive Models for Interpretable Deep Tabular Learning
Maximum Likelihood Estimation of Power-law Degree Distributions via Friendship Paradox-based Sampling
Probabilistic Modeling for Frequency Vectors Using a Flexible Shifted-Scaled Dirichlet Distribution Prior
Understanding and Guiding Weakly Supervised Entity Alignment with Potential Isomorphism Propagation
Listwise Learning to Rank from Crowds
Do We Really Need Imputation in AutoML Predictive Modeling?
Heterogeneous Network Approach to Predict Individuals' Mental Health
Joint Inference of Diffusion and Structure in Partially Observed Social Networks Using Coupled Matrix Factorization
On the Sample Complexity of Random Fourier Features for Online Learning: How Many Random Fourier Features Do We Need?
Neural Networks for Entity Matching: A Survey
On the Robustness of Metric Learning: An Adversarial Perspective
Identifying Complements and Substitutes of Products: A Neural Network Framework Based on Product Embedding
Coupled Clustering Ensemble by Exploring Data Interdependence
Unsupervised Head-Modifier Detection in Search Queries
Kernel Fisher Dictionary Transfer Learning
Heterogeneous Network Motif Coding, Counting, and Profiling
Mobile App Cross-Domain Recommendation with Multi-Graph Neural Network
Mining Top-k High On-shelf Utility Itemsets Using Novel Threshold Raising Strategies
ACM TKDD Special Issue on Knowledge Discovery for Web Intelligence
CenEEGs: Valid EEG Selection for Classification
Opinion Dynamics Optimization by Varying Susceptibility to Persuasion via Non-Convex Local Search
VOGUE: A variable order hidden Markov model with duration based on frequent sequence mining
Fast, Accurate, and Flexible Algorithms for Dense Subtensor Mining
VITR: Augmenting Vision Transformers with Relation-Focused Learning for Cross-modal Information Retrieval
Package Arrival Time Prediction via Knowledge Distillation Graph Neural Network
Sequential Modeling of Topic Dynamics with Multiple Timescales
Intent-aware Recommendation Based on Principal Component Analysis
STA-TCN: Spatial-temporal Attention over Temporal Convolutional Network for Next Point-of-interest Recommendation
Less is More: Building Selective Anomaly Ensembles
Exploring Deep Reinforcement Learning for Task Dispatching in Autonomous On-Demand Services
GRACE: A General Graph Convolution Framework for Attributed Graph Clustering
Protecting Privacy in Trajectories with a User-Centric Approach
Causal Feature Selection with Missing Data
Uncovering Hierarchical and Overlapping Communities with a Local-First Approach
Multi-view Ensemble Clustering via Low-rank and Sparse Decomposition: From Matrix to Tensor
Discrete Listwise Content-aware Recommendation
Finding Key Structures in MMORPG Graph with Hierarchical Graph Summarization
STHAN: Transportation Demand Forecasting with Compound Spatio-Temporal Relationships
Large-scale Data Exploration Using Explanatory Regression Functions
Story Forest: Extracting Events and Telling Stories from Breaking News
Multi-objective Learning to Overcome Catastrophic Forgetting in Time-series Applications
DisambiguART: A Neural-based Inference Model for Knowledge Graph Disambiguation
Modeling of Geographic Dependencies for Real Estate Ranking
A Relation-Constraint Link Prediction Model for Dynamic Knowledge Graphs with Entity Drift
Introduction to the Special Issue ACM SIGKDD 2012
Tensorizing Restricted Boltzmann Machine
Clustering aggregation
GOOWE: Geometrically Optimum and Online-Weighted Ensemble Classifier for Evolving Data Streams
Random Projections for Linear Support Vector Machines
ARIS: A Noise Insensitive Data Pre-Processing Scheme for Data Reduction Using Influence Space
Link Recommendation for Social Influence Maximization
Communication from the Editor-in-Chief: State of the ACM Transactions on Knowledge Discovery from Data
LoSAC: An Efficient Local Stochastic Average Control Method for Federated Optimization
SsAG: Summarization and Sparsification of Attributed Graphs
DEWP: Deep Expansion Learning for Wind Power Forecasting
Housing Demand Estimation Based on Express Delivery Data
Spatial-Temporal Data Mining for Ocean Science: Data, Methodologies and Opportunities
Spatial-Proximity Optimization for Rapid Task Group Deployment
Multi-task Crowdsourcing via an Optimization Framework
Clustering Heterogeneous Information Network by Joint Graph Embedding and Nonnegative Matrix Factorization
PSL: An Algorithm for Partial Bayesian Network Structure Learning
FastHGNN: A New Sampling Technique for Learning with Hypergraph Neural Networks
Prerequisite-Enhanced Category-Aware Graph Neural Networks for Course Recommendation
Trip Reinforcement Recommendation with Graph-based Representation Learning
In-Processing Modeling Techniques for Machine Learning Fairness: A Survey
Dual-View Learning from Crowds
Deep Learning-Based Energy Disaggregation and On/Off Detection of Household Appliances
Structured Sparse Boosting for Graph Classification
Triangle Centrality
Multi-Label Feature Selection Via Adaptive Label Correlation Estimation
Efficient Mining of Outlying Sequence Patterns for Analyzing Outlierness of Sequence Data
Hybrid Variational Autoencoder for Recommender Systems
Unbiased Measurement of Feature Importance in Tree-Based Methods
Incremental tensor analysis: Theory and applications
A Novel Graph Indexing Approach for Uncovering Potential COVID-19 Transmission Clusters
Efficient Nonnegative Tensor Factorization via Saturating Coordinate Descent
A Space-Efficient Streaming Algorithm for Estimating Transitivity and Triangle Counts Using the Birthday Paradox
On Proximity and Structural Role-based Embeddings in Networks: Misconceptions, Techniques, and Applications
Structure-Information-Based Reasoning over the Knowledge Graph: A Survey of Methods and Applications
Budget-Constrained Real-Time Bidding Optimization: Multiple Predictors Make It Better
Exploiting Pre-Trained Models and Low-Frequency Preference for Cost-Effective Transfer-based Attack
Exploiting Pre-Trained Language Models for Black-Box Attack against Knowledge Graph Embeddings
SIR-GN: A Fast Structural Iterative Representation Learning Approach For Graph Nodes
Expanding network communities from representative examples
Semi-supervised Multi-view Clustering based on NMF with Fusion Regularization
Exploring BCI Control in Smart Environments: Intention Recognition Via EEG Representation Enhancement Learning