wsdm 2021 论文列表
WSDM '21, The Fourteenth ACM International Conference on Web Search and Data Mining, Virtual Event, Israel, March 8-12, 2021.
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L2D 2021: First International Workshop on Enabling Data-Driven Decisions from Learning on the Web.
Overview of the Supporting and Understanding of Conversational Dialogues (SUD) Workshop.
The 1st International Workshop on Machine Reasoning: International Machine Reasoning Conference (MRC 2021).
Integrity 2021: Integrity in Social Networks and Media.
WebTour 2021 Workshop on Web Tourism.
Pretrained Transformers for Text Ranking: BERT and Beyond.
Neural Structured Learning: Training Neural Networks with Structured Signals.
Advances in Bias-aware Recommendation on the Web.
Information to Wisdom: Commonsense Knowledge Extraction and Compilation.
Scalable Graph Neural Networks with Deep Graph Library.
Beyond Probability Ranking Principle: Modeling the Dependencies among Documents.
WSDM 2021 Tutorial on Conversational Recommendation Systems.
WSDM 2021 Tutorial on Systematic Challenges and Computational Solutions on Bias and Unfairness in Peer Review.
Deep Learning for Anomaly Detection: Challenges, Methods, and Opportunities.
Personalization in Practice: Methods and Applications.
Towards Dynamic User Intention in Sequential Recommendation.
Graph Mining with Graph Neural Networks.
Fairness-Aware Recommendation in Multi-Sided Platforms.
Multimodal Machine Learning for Drug Knowledge Discovery.
Interpretability and Effectiveness of Machine Learning Methods for Sequence Mining in Various Domains.
Deep Recommender Systems Utilizing Side Information.
Multilingual and Multimodal Hate Speech Analysis in Twitter.
Data-Sharing Economy: Value-Addition from Data meets Privacy.
A Semantic Layer Querying Tool.
Evently: Modeling and Analyzing Reshare Cascades with Hawkes Processes.
Privacy Monitoring Service for Conversations.
Providing Actionable Feedback in Hiring Marketplaces using Generative Adversarial Networks.
AttentionFlow: Visualising Influence in Networks of Time Series.
Real-time Streaming of Gait Assessment for Parkinson's Disease.
Exploring Personal Knowledge Extraction from Conversations with CHARM.
Community Connect: A Mock Social Media Platform to Study Online Behavior.
All the Wiser: Fake News Intervention Using User Reading Preferences.
WoMG: A Library for Word-of-Mouth Cascades Generation.
Temporal Meta-path Guided Explainable Recommendation.
Toward User Engagement Optimization in 2D Presentation.
Heterogeneous Graph Augmented Multi-Scenario Sharing Recommendation with Tree-Guided Expert Networks.
Explanation as a Defense of Recommendation.
QueryBlazer: Efficient Query Autocompletion Framework.
Enhancing Neural Recommender Models through Domain-Specific Concordance.
Optimizing Multiple Performance Metrics with Deep GSP Auctions for E-commerce Advertising.
Multi-Interactive Attention Network for Fine-grained Feature Learning in CTR Prediction.
Mining the Stars: Learning Quality Ratings with User-facing Explanations for Vacation Rentals.
Explainable Recommendation with Comparative Constraints on Product Aspects.
Decomposed Collaborative Filtering: Modeling Explicit and Implicit Factors For Recommender Systems.
How to Measure Your App: A Couple of Pitfalls and Remedies in Measuring App Performance in Online Controlled Experiments.
β-Cores: Robust Large-Scale Bayesian Data Summarization in the Presence of Outliers.
Alleviating Cold-Start Problems in Recommendation through Pseudo-Labelling over Knowledge Graph.
DeepLight: Deep Lightweight Feature Interactions for Accelerating CTR Predictions in Ad Serving.
Birdspotter: A Tool for Analyzing and Labeling Twitter Users.
GPR: Global Personalized Restaurant Recommender System Leveraging Billions of Financial Transactions.
A Practical Federated Learning Framework for Small Number of Stakeholders.
AnaSearch: Extract, Retrieve and Visualize Structured Results from Unstructured Text for Analytical Queries.
Category Recognition in E-Commerce using Sequence-to-Sequence Hierarchical Classification.
WULAI-QA: Web Understanding and Learning with AI towards Document-based Question Answering against COVID-19.
ColorfulFeedback: Enhancing Interest Prediction Performance through Multi-dimensional Labeled Feedback from Users.
SoMin.ai: Personality-Driven Content Generation Platform.
TwiScraper: A Collaborative Project to Enhance Twitter Data Collection.
FinSense: An Assistant System for Financial Journalists and Investors.
I2PS: An Online Item Intelligent Publishing System in Consumer to Consumer (C2C) Transaction Platform.
Towards Scalable Spectral Embedding and Data Visualization via Spectral Coarsening.
HeteGCN: Heterogeneous Graph Convolutional Networks for Text Classification.
Modeling Context Pair Interaction for Pairwise Tasks on Graphs.
CalibreNet: Calibration Networks for Multilingual Sequence Labeling.
GraphSMOTE: Imbalanced Node Classification on Graphs with Graph Neural Networks.
FluxEV: A Fast and Effective Unsupervised Framework for Time-Series Anomaly Detection.
Joint Subgraph-to-Subgraph Transitions: Generalizing Triadic Closure for Powerful and Interpretable Graph Modeling.
Predicting Crowd Flows via Pyramid Dilated Deeper Spatial-temporal Network.
Unsupervised Attributed Network Embedding via Cross Fusion.
AutoCite: Multi-Modal Representation Fusion for Contextual Citation Generation.
Learning to Drop: Robust Graph Neural Network via Topological Denoising.
Hierarchical Metadata-Aware Document Categorization under Weak Supervision.
DeepIS: Susceptibility Estimation on Social Networks.
Balance Maximization in Signed Networks via Edge Deletions.
Exploring the Subgraph Density-Size Trade-off via the Lovaśz Extension.
Local Collaborative Autoencoders.
Heterogeneous Hypergraph Embedding for Graph Classification.
Learning User Representations with Hypercuboids for Recommender Systems.
Triangular Bidword Generation for Sponsored Search Auction.
Adversarial Immunization for Certifiable Robustness on Graphs.
A Unifying Framework to Identify Dense Subgraphs on Streams: Graph Nuclei to Hypergraph Cores.
Say No to the Discrimination: Learning Fair Graph Neural Networks with Limited Sensitive Attribute Information.
Fast Disjunctive Candidate Generation Using Live Block Filtering.
Federated Deep Knowledge Tracing.
Filter Pruning via Probabilistic Model-based Optimization for Accelerating Deep Convolutional Neural Networks.
Centrality with Diversity.
Bipartite Graph Embedding via Mutual Information Maximization.
Modeling Inter-station Relationships with Attentive Temporal Graph Convolutional Network for Air Quality Prediction.
Explainable Multivariate Time Series Classification: A Deep Neural Network Which Learns to Attend to Important Variables As Well As Time Intervals.
Sparse-Interest Network for Sequential Recommendation.
F-FADE: Frequency Factorization for Anomaly Detection in Edge Streams.
Time-Series Event Prediction with Evolutionary State Graph.
Long Horizon Forecasting with Temporal Point Processes.
Beyond Relevance: Trustworthy Answer Selection via Consensus Verification.
Improving Multi-hop Knowledge Base Question Answering by Learning Intermediate Supervision Signals.
Personalized Food Recommendation as Constrained Question Answering over a Large-scale Food Knowledge Graph.
Learning Dynamic Embeddings for Temporal Knowledge Graphs.
FACE-KEG: Fact Checking Explained using KnowledgE Graphs.
Temporal Cross-Effects in Knowledge Tracing.
Improving Cloud Storage Search with User Activity.
Interpretable Ranking with Generalized Additive Models.
Unbiased Learning to Rank in Feeds Recommendation.
Non-Clicks Mean Irrelevant? Propensity Ratio Scoring As a Correction.
Bias-Variance Decomposition for Ranking.
Unifying Online and Counterfactual Learning to Rank: A Novel Counterfactual Estimator that Effectively Utilizes Online Interventions.
Online Post-Processing in Rankings for Fair Utility Maximization.
Towards Long-term Fairness in Recommendation.
Practical Compositional Fairness: Understanding Fairness in Multi-Component Recommender Systems.
Combating Selection Biases in Recommender Systems with a Few Unbiased Ratings.
Explain and Predict, and then Predict Again.
Split-Treatment Analysis to Rank Heterogeneous Causal Effects for Prospective Interventions.
An Efficient and Effective Framework for Session-based Social Recommendation.
Event-Driven Query Expansion.
Origin-Aware Next Destination Recommendation with Personalized Preference Attention.
Denoising Implicit Feedback for Recommendation.
Adapting User Preference to Online Feedback in Multi-round Conversational Recommendation.
Question Rewriting for Conversational Question Answering.
Contextualizing Trending Entities in News Stories.
Abstractive Opinion Tagging.
Quotebank: A Corpus of Quotations from a Decade of News.
Discovering Undisclosed Paid Partnership on Social Media via Aspect-Attentive Sponsored Post Learning.
Generating Tips from Product Reviews.
Generative Models are Unsupervised Predictors of Page Quality: A Colossal-Scale Study.
Bilateral Variational Autoencoder for Collaborative Filtering.
PROP: Pre-training with Representative Words Prediction for Ad-hoc Retrieval.
Long-Term Effect Estimation with Surrogate Representation.
Pre-Training Graph Neural Networks for Cold-Start Users and Items Representation.
Theoretical Understandings of Product Embedding for E-commerce Machine Learning.
Chebyshev Accelerated Spectral Clustering.
Shifting Consumption towards Diverse Content on Music Streaming Platforms.
Credit Risk and Limits Forecasting in E-Commerce Consumer Lending Service via Multi-view-aware Mixture-of-experts Nets.
Relation-aware Meta-learning for E-commerce Market Segment Demand Prediction with Limited Records.
Causal Transfer Random Forest: Combining Logged Data and Randomized Experiments for Robust Prediction.
CONQ: CONtinuous Quantile Treatment Effects for Large-Scale Online Controlled Experiments.
Online Experimentation with Surrogate Metrics: Guidelines and a Case Study.
Learning and Updating Node Embedding on Dynamic Heterogeneous Information Network.
Balanced Influence Maximization in the Presence of Homophily.
Deconfounding with Networked Observational Data in a Dynamic Environment.
BiTe-GCN: A New GCN Architecture via Bidirectional Convolution of Topology and Features on Text-Rich Networks.
Node Similarity Preserving Graph Convolutional Networks.
RePBubLik: Reducing Polarized Bubble Radius with Link Insertions.
Diverse User Preference Elicitation with Multi-Armed Bandits.
User Response Models to Improve a REINFORCE Recommender System.
Real-time Relevant Recommendation Suggestion.
Leave No User Behind: Towards Improving the Utility of Recommender Systems for Non-mainstream Users.
A Black-Box Attack Model for Visually-Aware Recommender Systems.
Popularity-Opportunity Bias in Collaborative Filtering.
Beyond Point Estimate: Inferring Ensemble Prediction Variation from Neuron Activation Strength in Recommender Systems.
On the Impact of Predicate Complexity in Crowdsourced Classification Tasks.
Modeling Across-Context Attention For Long-Tail Query Classification in E-commerce.
DECAF: Deep Extreme Classification with Label Features.
Semi-Supervised Text Classification via Self-Pretraining.
DeepXML: A Deep Extreme Multi-Label Learning Framework Applied to Short Text Documents.
Towards Ordinal Suicide Ideation Detection on Social Media.
Ad Delivery Algorithms: The Hidden Arbiters of Political Messaging.
Population-Scale Study of Human Needs During the COVID-19 Pandemic: Analysis and Implications.
Harnessing Big Data for Personalized Medicine.
Beyond Web Search: How Email Search is Different and Why it Matters.
Some Thoughts on Computational Natural Language in the 21st Century.
