wsdm 2020 论文列表
WSDM '20: The Thirteenth ACM International Conference on Web Search and Data Mining, Houston, TX, USA, February 3-7, 2020.
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Learning from Heterogeneous Networks: Methods and Applications.
Overlapping Community Detection in Static and Dynamic Networks.
Hybrid Utility Function for Unexpected Recommendations.
Think like a Human: Constructing Cognitive-oriented Retrieval Model for Web Search.
Decision Boundary of Deep Neural Networks: Challenges and Opportunities.
Network Analysis with Negative Links.
Beyond Sessions: Exploiting Hybrid Contextual Information for Web Search.
Temporal Pattern of Retweet(s) Help to Maximize Information Diffusion in Twitter.
User Intent Inference for Web Search and Conversational Agents.
Impact of Online Job Search and Job Reviews on Job Decision.
NLP4REC: The WSDM 2020 Workshop on Natural Language Processing for Recommendations.
Integrity 2020: Integrity in Social Networks and Media.
Workshop on Privacy in NLP (PrivateNLP 2020).
Overview of the Health Search and Data Mining (HSDM 2020) Workshop.
SUM'20: State-based User Modelling.
ConvERSe'20: The WSDM 2020 Workshop on Conversational Systems for E-Commerce Recommendations and Search.
Deep Learning for Anomaly Detection.
Learning and Reasoning on Graph for Recommendation.
Web-scale Knowledge Collection.
Learning with Small Data.
Intelligible Machine Learning and Knowledge Discovery Boosted by Visual Means.
Challenges, Best Practices and Pitfalls in Evaluating Results of Online Controlled Experiments.
Practice of Efficient Data Collection via Crowdsourcing: Aggregation, Incremental Relabelling, and Pricing.
Adversarial Machine Learning in Recommender Systems (AML-RecSys).
Deep Bayesian Data Mining.
Capreolus: A Toolkit for End-to-End Neural Ad Hoc Retrieval.
VISION-KG: Topic-centric Visualization System for Summarizing Knowledge Graph.
SPread: Automated Financial Metric Extraction and Spreading Tool from Earnings Reports.
Illustrate Your Story: Enriching Text with Images.
OpenNIR: A Complete Neural Ad-Hoc Ranking Pipeline.
Athena: A Ranking Enabled Scholarly Search System.
WebShapes: Network Visualization with 3D Shapes.
Entities with Quantities: Extraction, Search, and Ranking.
FAQAugmenter: Suggesting Questions for Enterprise FAQ Pages.
personality2vec: Enabling the Analysis of Behavioral Disorders in Social Networks.
Pseudo Dyna-Q: A Reinforcement Learning Framework for Interactive Recommendation.
Sequential Modeling of Hierarchical User Intention and Preference for Next-item Recommendation.
Listwise Learning to Rank by Exploring Unique Ratings.
Enhancing Re-finding Behavior with External Memories for Personalized Search.
GREASE: A Generative Model for Relevance Search over Knowledge Graphs.
Investigating Examination Behavior in Mobile Search.
Improving the Estimation of Tail Ratings in Recommender System with Multi-Latent Representations.
Temporal Context-Aware Representation Learning for Question Routing.
AutoBlock: A Hands-off Blocking Framework for Entity Matching.
Distilling Structured Knowledge into Embeddings for Explainable and Accurate Recommendation.
Nearly Linear Time Algorithm for Mean Hitting Times of Random Walks on a Graph.
Learning a Joint Search and Recommendation Model from User-Item Interactions.
Sampling Subgraphs with Guaranteed Treewidth for Accurate and Efficient Graphical Inference.
Relation Learning on Social Networks with Multi-Modal Graph Edge Variational Autoencoders.
Model Compression with Two-stage Multi-teacher Knowledge Distillation for Web Question Answering System.
Knowledge-aware Complementary Product Representation Learning.
Product Knowledge Graph Embedding for E-commerce.
PERQ: Predicting, Explaining, and Rectifying Failed Questions in KB-QA Systems.
Metrics, User Models, and Satisfaction.
Time to Shop for Valentine's Day: Shopping Occasions and Sequential Recommendation in E-commerce.
Key Opinion Leaders in Recommendation Systems: Opinion Elicitation and Diffusion.
User Recommendation in Content Curation Platforms.
Addressing Marketing Bias in Product Recommendations.
HyperML: A Boosting Metric Learning Approach in Hyperbolic Space for Recommender Systems.
Transferring Robustness for Graph Neural Network Against Poisoning Attacks.
Fast Item Ranking under Neural Network based Measures.
LARA: Attribute-to-feature Adversarial Learning for New-item Recommendation.
Influence Maximization with Spontaneous User Adoption.
Label Distribution Augmented Maximum Likelihood Estimation for Reading Comprehension.
ADMM SLIM: Sparse Recommendations for Many Users.
Ad Close Mitigation for Improved User Experience in Native Advertisements.
Text Recognition Using Anonymous CAPTCHA Answers.
RecVAE: A New Variational Autoencoder for Top-N Recommendations with Implicit Feedback.
DySAT: Deep Neural Representation Learning on Dynamic Graphs via Self-Attention Networks.
Inf-VAE: A Variational Autoencoder Framework to Integrate Homophily and Influence in Diffusion Prediction.
Unbiased Recommender Learning from Missing-Not-At-Random Implicit Feedback.
Toward Activity Discovery in the Personal Web.
A Structural Graph Representation Learning Framework.
Stepwise Reasoning for Multi-Relation Question Answering over Knowledge Graph with Weak Supervision.
Sequential Recommendation with Dual Side Neighbor-based Collaborative Relation Modeling.
Extreme Regression for Dynamic Search Advertising.
Efficiently Counting Vertex Orbits of All 5-vertex Subgraphs, by EVOKE.
Predicting Human Mobility via Attentive Convolutional Network.
Separate and Attend in Personal Email Search.
MRAEA: An Efficient and Robust Entity Alignment Approach for Cross-lingual Knowledge Graph.
Beyond Statistical Relations: Integrating Knowledge Relations into Style Correlations for Multi-Label Music Style Classification.
Jointly Optimized Neural Coreference Resolution with Mutual Attention.
Deep Multi-Graph Clustering via Attentive Cross-Graph Association.
End-to-End Deep Reinforcement Learning based Recommendation with Supervised Embedding.
Balanced Influence Maximization in Attributed Social Network Based on Sampling.
Initialization for Network Embedding: A Graph Partition Approach.
Incremental Filter Pruning via Random Walk for Accelerating Deep Convolutional Neural Networks.
Adversarial Learning to Compare: Self-Attentive Prospective Customer Recommendation in Location based Social Networks.
Automatic Speaker Recognition with Limited Data.
DDTCDR: Deep Dual Transfer Cross Domain Recommendation.
Time Interval Aware Self-Attention for Sequential Recommendation.
Interpretable Click-Through Rate Prediction through Hierarchical Attention.
Estimation-Action-Reflection: Towards Deep Interaction Between Conversational and Recommender Systems.
Retrieving Top Weighted Triangles in Graphs.
Modeling Information Cascades with Self-exciting Processes via Generalized Epidemic Models.
Ultra Fine-Grained Image Semantic Embedding.
The Power of Pivoting for Exact Clique Counting.
Debiasing Word Embeddings from Sentiment Associations in Names.
Consistency-Aware Recommendation for User-Generated Item List Continuation.
Crowd Worker Strategies in Relevance Judgment Tasks.
Learning Individual Causal Effects from Networked Observational Data.
Hierarchical User Profiling for E-commerce Recommender Systems.
TSA: A Truthful Mechanism for Social Advertising.
JNET: Learning User Representations via Joint Network Embedding and Topic Embedding.
PRINCE: Provider-side Interpretability with Counterfactual Explanations in Recommender Systems.
Recurrent Memory Reasoning Network for Expert Finding in Community Question Answering.
Privacy- and Utility-Preserving Textual Analysis via Calibrated Multivariate Perturbations.
All You Need Is Low (Rank): Defending Against Adversarial Attacks on Graphs.
Epidemic Graph Convolutional Network.
Meta-Learning with Dynamic-Memory-Based Prototypical Network for Few-Shot Event Detection.
Can A User Guess What Her Followers Want?
Joint Recognition of Names and Publications in Academic Homepages.
ENTYFI: Entity Typing in Fictional Texts.
Analyzing the Impact of Filter Bubbles on Social Network Polarization.
Context-aware Deep Model for Joint Mobility and Time Prediction.
Parameter Tuning in Personal Search Systems.
A Context-Aware Click Model for Web Search.
Why Do People Buy Seemingly Irrelevant Items in Voice Product Search?: On the Relation between Product Relevance and Customer Satisfaction in eCommerce.
Popularity Prediction on Social Platforms with Coupled Graph Neural Networks.
A Stochastic Treatment of Learning to Rank Scoring Functions.
Comparative Web Search Questions.
LouvainNE: Hierarchical Louvain Method for High Quality and Scalable Network Embedding.
Privacy-Aware Recommendation with Private-Attribute Protection using Adversarial Learning.
Outlier Resistant Unsupervised Deep Architectures for Attributed Network Embedding.
Recurrent Attention Walk for Semi-supervised Classification.
Language-Agnostic Representation Learning for Product Search on E-Commerce Platforms.
Can Deep Learning Only Be Neural Networks?
Veridical Data Science.
Computer Vision for Fashion: From Individual Recommendations to World-wide Trends.
From Missing Data to Boltzmann Distributions and Time Dynamics: The Statistical Physics of Recommendation.
