wsdm 2022 论文列表
WSDM '22: The Fifteenth ACM International Conference on Web Search and Data Mining, Virtual Event / Tempe, AZ, USA, February 21 - 25, 2022.
|
The Rise of Data Observability: Architecting the Future of Data Trust.
Graph Neural Networks for the Global Economy with Microsoft DeepGraph.
The Incentives Platform at Lyft.
Rethink e-Commerce Search.
Challenges in Data Production for AI with Human-in-the-Loop.
Experiments with Predictive Long Term Guardrail Metrics.
Successes and Opportunities in Enterprise AI.
Near Real Time AI Personalization for Notifications at LinkedIn.
Mining Frequent Patterns on Knowledge Graphs.
A Practical Guide to Robust Multimodal Machine Learning and Its Application in Education.
Scalable Attribute Extraction at Instacart.
AI & Public Data for Humanitarian and Emergency Response.
Studying Long-Term User Behaviour Using Dynamic Time Warping for Customer Retention.
Exploration in Recommender Systems.
Towards a Cross-domain Semantically Interoperable Ecosystem.
Predicting Users' Gender and Age based on Mobile Tasks.
The Pit Stop Problem: How to Plan Your Next Road Trip.
Modern Theoretical Tools for Understanding and Designing Next-generation Information Retrieval System.
Fact-Checking, Fake News, Propaganda, Media Bias, and the COVID-19 Infodemic.
Half-Day Tutorial on Combating Online Hate Speech: The Role of Content, Networks, Psychology, User Behavior, etc.
A Tutorial on Stance Detection.
Graph Neural Networks for Recommender System.
Graph Minimally-supervised Learning.
Search and Discovery in Personal Email Collections.
Personalized Information Retrieval for Touristic Attractions in Augmented Reality.
An Interactive Knowledge Graph Based Platform for COVID-19 Clinical Research.
Crowd_Frame: A Simple and Complete Framework to Deploy Complex Crowdsourcing Tasks Off-the-shelf.
Fair-SRS: A Fair Session-based Recommendation System.
RGRecSys: A Toolkit for Robustness Evaluation of Recommender Systems.
PrivacyCheck v3: Empowering Users with Higher-Level Understanding of Privacy Policies.
Node Co-occurrence based Graph Neural Networks for Knowledge Graph Link Prediction.
a2RegInf: An Interactive System for Maximizing Influence within Arbitrary Number of Arbitrary Shaped Query Regions.
Automating ETL and Mining of Ethereum Blockchain Network.
Building Multi-turn Query Interpreters for E-commercial Chatbots with Sparse-to-dense Attentive Modeling.
Aligning the Research and Practice of Building Search Applications: Elasticsearch and Pyserini.
Web Search via an Efficient and Effective Brain-Machine Interface.
iLFQA: A Platform for Efficient and Accurate Long-Form Question Answering.
Quality Assurance of a German COVID-19 Question Answering Systems using Component-based Microbenchmarking.
Doctoral Consortium of WSDM'22: Exploring the Bias of Adversarial Defenses.
Fair Graph Representation Learning with Imbalanced and Biased Data.
Obtaining Robust Models from Imbalanced Data.
Trustworthy Machine Learning: Fairness and Robustness.
From Uni-relational to Multi-relational Graph Neural Networks.
Towards Practical Robustness Evaluation and Robustness Enhancing.
GNNs for Node Clustering in Signed and Directed Networks.
Robust Graph Learning for Misbehavior Detection.
Improving Text Generation via Neural Discourse Planning.
Improving Session Search by Modeling Multi-Granularity Historical Query Change.
A Neighborhood-Attention Fine-grained Entity Typing for Knowledge Graph Completion.
DualDE: Dually Distilling Knowledge Graph Embedding for Faster and Cheaper Reasoning.
Personalized Transfer of User Preferences for Cross-domain Recommendation.
Fighting Mainstream Bias in Recommender Systems via Local Fine Tuning.
C²-CRS: Coarse-to-Fine Contrastive Learning for Conversational Recommender System.
Learning Transferable Node Representations for Attribute Extraction from Web Documents.
AngHNE: Representation Learning for Bipartite Heterogeneous Networks with Angular Loss.
Joint Learning of E-commerce Search and Recommendation with a Unified Graph Neural Network.
Multi-Sparse-Domain Collaborative Recommendation via Enhanced Comprehensive Aspect Preference Learning.
ST-GSP: Spatial-Temporal Global Semantic Representation Learning for Urban Flow Prediction.
Towards Fair Classifiers Without Sensitive Attributes: Exploring Biases in Related Features.
A Counterfactual Modeling Framework for Churn Prediction.
PipAttack: Poisoning Federated Recommender Systems for Manipulating Item Promotion.
CMT-Net: A Mutual Transition Aware Framework for Taxicab Pick-ups and Drop-offs Co-Prediction.
GraSP: Optimizing Graph-based Nearest Neighbor Search with Subgraph Sampling and Pruning.
A GNN-based Multi-task Learning Framework for Personalized Video Search.
Learning Concept Prerequisite Relations from Educational Data via Multi-Head Attention Variational Graph Auto-Encoders.
Leaving No One Behind: A Multi-Scenario Multi-Task Meta Learning Approach for Advertiser Modeling.
MotifClass: Weakly Supervised Text Classification with Higher-order Metadata Information.
ESC-GAN: Extending Spatial Coverage of Physical Sensors.
Geometric Inductive Matrix Completion: A Hyperbolic Approach with Unified Message Passing.
Learning Discrete Representations via Constrained Clustering for Effective and Efficient Dense Retrieval.
Community Trend Prediction on Heterogeneous Graph in E-commerce.
Sentiment Analysis of Fashion Related Posts in Social Media.
Bringing Your Own View: Graph Contrastive Learning without Prefabricated Data Augmentations.
Directed Network Embedding with Virtual Negative Edges.
Assessing Algorithmic Biases for Musical Version Identification.
Fast Semantic Matching via Flexible Contextualized Interaction.
Interpretable Relation Learning on Heterogeneous Graphs.
MAVE: A Product Dataset for Multi-source Attribute Value Extraction.
Few-shot Link Prediction in Dynamic Networks.
Lightweight Composite Re-Ranking for Efficient Keyword Search with BERT.
Translating Human Mobility Forecasting through Natural Language Generation.
MAF: A General Matching and Alignment Framework for Multimodal Named Entity Recognition.
Identifying Cost-effective Debunkers for Multi-stage Fake News Mitigation Campaigns.
Informed Multi-context Entity Alignment.
Supervised Advantage Actor-Critic for Recommender Systems.
A Peep into the Future: Adversarial Future Encoding in Recommendation.
Long Short-Term Temporal Meta-learning in Online Recommendation.
Towards Unbiased and Robust Causal Ranking for Recommender Systems.
Improving the Applicability of Knowledge-Enhanced Dialogue Generation Systems by Using Heterogeneous Knowledge from Multiple Sources.
Crowdsourcing-based Multi-Device Communication Cooperation for Mobile High-Quality Video Enhancement.
A Cooperative-Competitive Multi-Agent Framework for Auto-bidding in Online Advertising.
Contrastive Meta Learning with Behavior Multiplicity for Recommendation.
Profiling the Design Space for Graph Neural Networks based Collaborative Filtering.
Scalable Graph Topology Learning via Spectral Densification.
Structure Meets Sequences: Predicting Network of Co-evolving Sequences.
Hierarchical Imitation Learning via Subgoal Representation Learning for Dynamic Treatment Recommendation.
Personalized Long-distance Fuel-efficient Route Recommendation Through Historical Trajectories Mining.
A Sequence-to-Sequence Model for Large-scale Chinese Abbreviation Database Construction.
MtCut: A Multi-Task Framework for Ranked List Truncation.
Knowledge Enhanced Sports Game Summarization.
Learning-To-Ensemble by Contextual Rank Aggregation in E-Commerce.
A New Class of Polynomial Activation Functions of Deep Learning for Precipitation Forecasting.
DAME: Domain Adaptation for Matching Entities.
Friend Story Ranking with Edge-Contextual Local Graph Convolutions.
Uncovering Causal Effects of Online Short Videos on Consumer Behaviors.
Graph Few-shot Class-incremental Learning.
MonLAD: Money Laundering Agents Detection in Transaction Streams.
Efficient Reachability Query with Extreme Labeling Filter.
Choosing the Best of Both Worlds: Diverse and Novel Recommendations through Multi-Objective Reinforcement Learning.
Show Me the Whole World: Towards Entire Item Space Exploration for Interactive Personalized Recommendations.
Sequential Modeling with Multiple Attributes for Watchlist Recommendation in E-Commerce.
Attributed Graph Modeling with Vertex Replacement Grammars.
Using Conjunctions for Faster Disjunctive Top-k Queries.
Finding a Concise, Precise, and Exhaustive Set of Near Bi-Cliques in Dynamic Graphs.
Diversified Query Generation Guided by Knowledge Graph.
Evaluating Mixed-initiative Conversational Search Systems via User Simulation.
Retrieving Black-box Optimal Images from External Databases.
Enumerating Fair Packages for Group Recommendations.
Understanding and Mitigating the Effect of Outliers in Fair Ranking.
On Sampling Collaborative Filtering Datasets.
Time Masking for Temporal Language Models.
A Simple but Effective Bidirectional Framework for Relational Triple Extraction.
Contrastive Learning for Representation Degeneration Problem in Sequential Recommendation.
Scope-aware Re-ranking with Gated Attention in Feed.
EvoKG: Jointly Modeling Event Time and Network Structure for Reasoning over Temporal Knowledge Graphs.
Reinforcement Learning over Sentiment-Augmented Knowledge Graphs towards Accurate and Explainable Recommendation.
Heterogeneous Global Graph Neural Networks for Personalized Session-based Recommendation.
Reconfiguration Problems on Submodular Functions.
MTLTS: A Multi-Task Framework To Obtain Trustworthy Summaries From Crisis-Related Microblogs.
Learning Relevant Questions for Conversational Product Search using Deep Reinforcement Learning.
Speaker and Time-aware Joint Contextual Learning for Dialogue-act Classification in Counselling Conversations.
Pretraining Multi-modal Representations for Chinese NER Task with Cross-Modality Attention.
Fast Learning of MNL Model from General Partial Rankings with Application to Network Formation Modeling.
Deep Graph-level Anomaly Detection by Glocal Knowledge Distillation.
Learning Fair Node Representations with Graph Counterfactual Fairness.
Diversified Subgraph Query Generation with Group Fairness.
Adversarial Attack on Graph Neural Networks as An Influence Maximization Problem.
VAE++: Variational AutoEncoder for Heterogeneous One-Class Collaborative Filtering.
ComGA: Community-Aware Attributed Graph Anomaly Detection.
RLMob: Deep Reinforcement Learning for Successive Mobility Prediction.
Ada-GNN: Adapting to Local Patterns for Improving Graph Neural Networks.
The Multi-vehicle Ride-Sharing Problem.
Non-stationary Continuum-armed Bandits for Online Hyperparameter Optimization.
An Ensemble Model for Combating Label Noise.
Improving Knowledge Tracing with Collaborative Information.
Surrogate Representation Learning with Isometric Mapping for Gray-box Graph Adversarial Attacks.
Graph Embedding with Hierarchical Attentive Membership.
RecGURU: Adversarial Learning of Generalized User Representations for Cross-Domain Recommendation.
Unsupervised Cross-Domain Adaptation for Response Selection Using Self-Supervised and Adversarial Training.
A Cooperative Neural Information Retrieval Pipeline with Knowledge Enhanced Automatic Query Reformulation.
Collaborative Curating for Discovery and Expansion of Visual Clusters.
Differential Query Semantic Analysis: Discovery of Explicit Interpretable Knowledge from E-Com Search Logs.
Efficient Two-stage Label Noise Reduction for Retrieval-based Tasks.
Linear, or Non-Linear, That is the Question!
Multi-Resolution Attention for Personalized Item Search.
Introducing the Expohedron for Efficient Pareto-optimal Fairness-Utility Amortizations in Repeated Rankings.
Doubly Robust Off-Policy Evaluation for Ranking Policies under the Cascade Behavior Model.
Cluster-Aware Heterogeneous Information Network Embedding.
ConsistSum: Unsupervised Opinion Summarization with the Consistency of Aspect, Sentiment and Semantic.
An Unsupervised Detection Framework for Chinese Jargons in the Darknet.
Query Interpretations from Entity-Linked Segmentations.
GAGE: Geometry Preserving Attributed Graph Embeddings.
Leveraging World Events to Predict E-Commerce Consumer Demand under Anomaly.
KGNN: Harnessing Kernel-based Networks for Semi-supervised Graph Classification.
On Generalizing Static Node Embedding to Dynamic Settings.
Triangle Graph Interest Network for Click-through Rate Prediction.
POLE: Polarized Embedding for Signed Networks.
It Is Different When Items Are Older: Debiasing Recommendations When Selection Bias and User Preferences Are Dynamic.
Keyword Assisted Embedded Topic Model.
Dy-HIEN: Dynamic Evolution based Deep Hierarchical Intention Network for Membership Prediction.
Outside In: Market-aware Heterogeneous Graph Neural Network for Employee Turnover Prediction.
Learning Multi-granularity Consecutive User Intent Unit for Session-based Recommendation.
Multi-Scale Variational Graph AutoEncoder for Link Prediction.
Differentially Private Ensemble Classifiers for Data Streams.
Toward Pareto Efficient Fairness-Utility Trade-off in Recommendation through Reinforcement Learning.
HeteroQA: Learning towards Question-and-Answering through Multiple Information Sources via Heterogeneous Graph Modeling.
Leveraging Multi-view Inter-passage Interactions for Neural Document Ranking.
Efficient Graph Convolution for Joint Node Representation Learning and Clustering.
How Do You Test a Test?: A Multifaceted Examination of Significance Tests.
Variational User Modeling with Slow and Fast Features.
Modeling Users' Contextualized Page-wise Feedback for Click-Through Rate Prediction in E-commerce Search.
External Evaluation of Ranking Models under Extreme Position-Bias.
Semi-supervised Stance Detection of Tweets Via Distant Network Supervision.
Understanding and Improvement of Adversarial Training for Network Embedding from an Optimization Perspective.
Combinatorial Bandits under Strategic Manipulations.
Improving Personalized Search with Dual-Feedback Network.
Deep-QPP: A Pairwise Interaction-based Deep Learning Model for Supervised Query Performance Prediction.
Predicting Human Mobility via Graph Convolutional Dual-attentive Networks.
Towards Robust Graph Neural Networks for Noisy Graphs with Sparse Labels.
Beyond NED: Fast and Effective Search Space Reduction for Complex Question Answering over Knowledge Bases.
ANTHEM: Attentive Hyperbolic Entity Model for Product Search.
S-Walk: Accurate and Scalable Session-based Recommendation with Random Walks.
The Datasets Dilemma: How Much Do We Really Know About Recommendation Datasets?
An Adaptive Unified Allocation Framework for Guaranteed Display Advertising.
AdaptKT: A Domain Adaptable Method for Knowledge Tracing.
Causal Mediation Analysis with Hidden Confounders.
Estimating Causal Effects of Multi-Aspect Online Reviews with Multi-Modal Proxies.
Modeling Scale-free Graphs with Hyperbolic Geometry for Knowledge-aware Recommendation.
A Personalized Cross-Platform Post Style Transfer Method Based on Transformer and Bi-Attention Mechanism.
Graph Collaborative Reasoning.
Towards Understanding and Answering Comparative Questions.
CAN: Feature Co-Action Network for Click-Through Rate Prediction.
'It's on the tip of my tongue': A new Dataset for Known-Item Retrieval.
Sampling Multiple Nodes in Large Networks: Beyond Random Walks.
Harvesting More Answer Spans from Paragraph beyond Annotation.
Wikipedia Reader Navigation: When Synthetic Data Is Enough.
k-Clustering with Fair Outliers.
Graph Neural Network Research at AWS AI.
Knowledge is Power: Symbolic Knowledge Distillation, Commonsense Morality, & Multimodal Script Knowledge.
Ethical Challenges in AI.
