wsdm 2019 论文列表
Proceedings of the Twelfth ACM International Conference on Web Search and Data Mining, WSDM 2019, Melbourne, VIC, Australia, February 11-15, 2019.
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Task Intelligence Workshop @ WSDM 2019.
IDM-WSDM 2019: Workshop on Interactive Data Mining.
DAPA: The WSDM 2019 Workshop on Deep Matching in Practical Applications.
The 1st International Workshop on Context-Aware Recommendation Systems with Big Data Analytics (CARS-BDA).
Privacy-preserving Data Mining in Industry.
WSDM 2019 Tutorial on Health Search (HS2019): A Full-Day from Consumers to Clinicians.
Fake News: Fundamental Theories, Detection Strategies and Challenges.
Fairness-Aware Machine Learning: Practical Challenges and Lessons Learned.
Deep Learning for Matching in Search and Recommendation.
Conducting Laboratory Experiments Properly with Statistical Tools: An Easy Hands-On Tutorial.
Causal Inference and Counterfactual Reasoning (3hr Tutorial).
User Behavior Modeling for Web Image Search.
Preference Elicitation Strategy for Conversational Recommender System.
Overlapping Community Detection in Static and Dynamic Social Networks.
Listwise vs Pagewise: Towards Better Ranking Strategies for Heterogeneous Search Results.
Linking Epidemic Models and Hawkes Point Processes for Modeling Information Diffusion.
How is Attention Allocated?: Data-Driven Studies of Popularity and Engagement in Online Videos.
Designing the Cogno-Web Observatory: To Characterize the Dynamics of Online Social Cognition.
Comparative Summarisation of Rich Media Collections.
Bridging Models for Popularity Prediction on Social Media.
Visualizing Graph Differences from Social Media Streams.
VisCrime: A Crime Visualisation System for Crime Trajectory from Multi-Dimensional Sources.
TopExNet: Entity-Centric Network Topic Exploration in News Streams.
Structured Search in Annotated Document Collections.
NAIRS: A Neural Attentive Interpretable Recommendation System.
Pleasant Route Suggestion based on Color and Object Rates.
Interactive Visualization of Urban Areas of Interest: A Parameter-Free and Efficient Footprint Method.
Intelligent Traffic Analytics: From Monitoring to Controlling.
FaceOff: Assisting the Manifestation Design of Web Graphical User Interface.
EXS: Explainable Search Using Local Model Agnostic Interpretability.
clstk: The Cross-Lingual Summarization Tool-Kit.
ATAR: Aspect-Based Temporal Analog Retrieval System for Document Archives.
CluWords: Exploiting Semantic Word Clustering Representation for Enhanced Topic Modeling.
Crosslingual Document Embedding as Reduced-Rank Ridge Regression.
Across-Time Comparative Summarization of News Articles.
Discovering Correlations between Sparse Features in Distant Supervision for Relation Extraction.
Solving the Sparsity Problem in Recommendations via Cross-Domain Item Embedding Based on Co-Clustering.
Spring-Electrical Models For Link Prediction.
Learning to Selectively Transfer: Reinforced Transfer Learning for Deep Text Matching.
SHNE: Representation Learning for Semantic-Associated Heterogeneous Networks.
Learning to Transform, Combine, and Reason in Open-Domain Question Answering.
Domain Adaptation for Commitment Detection in Email.
Domain Switch-Aware Holistic Recurrent Neural Network for Modeling Multi-Domain User Behavior.
Neural Demographic Prediction using Search Query.
The Influence of Image Search Intents on User Behavior and Satisfaction.
Task Duration Estimation.
Characterizing and Predicting Email Deferral Behavior.
Why the World Reads Wikipedia: Beyond English Speakers.
Learning Personalized Topical Compositions with Item Response Theory.
Sequential Variational Autoencoders for Collaborative Filtering.
Time is of the Essence: A Joint Hierarchical RNN and Point Process Model for Time and Item Predictions.
A Simple Convolutional Generative Network for Next Item Recommendation.
Taxonomy-Aware Multi-Hop Reasoning Networks for Sequential Recommendation.
Recurrent Recommendation with Local Coherence.
Session-Based Social Recommendation via Dynamic Graph Attention Networks.
Shaping Feedback Data in Recommender Systems with Interventions Based on Information Foraging Theory.
Neural Tensor Factorization for Temporal Interaction Learning.
Slice: Scalable Linear Extreme Classifiers Trained on 100 Million Labels for Related Searches.
Gated Attentive-Autoencoder for Content-Aware Recommendation.
Investment Recommendation System for Low-Liquidity Online Peer to Peer Lending (P2PL) Marketplaces.
How A/B Tests Could Go Wrong: Automatic Diagnosis of Invalid Online Experiments.
A Sequential Test for Selecting the Better Variant: Online A/B testing, Adaptive Allocation, and Continuous Monitoring.
Off-Policy Evaluation of Probabilistic Identity Data in Lookalike Modeling.
Estimating Position Bias without Intrusive Interventions.
Genie: An Open Box Counterfactual Policy Estimator for Optimizing Sponsored Search Marketplace.
Top-K Off-Policy Correction for a REINFORCE Recommender System.
When People Change their Mind: Off-Policy Evaluation in Non-stationary Recommendation Environments.
Linked Variational AutoEncoders for Inferring Substitutable and Supplementary Items.
Product-Aware Answer Generation in E-Commerce Question-Answering.
Offline Evaluation to Make Decisions About PlaylistRecommendation Algorithms.
Review-Driven Answer Generation for Product-Related Questions in E-Commerce.
Weakly Supervised Co-Training of Query Rewriting andSemantic Matching for e-Commerce.
Co-Embedding Attributed Networks.
SimGNN: A Neural Network Approach to Fast Graph Similarity Computation.
A General View for Network Embedding as Matrix Factorization.
Random Spatial Network Models for Core-Periphery Structure.
Interactive Anomaly Detection on Attributed Networks.
Homogeneity-Based Transmissive Process to Model True and False News in Social Networks.
XBully: Cyberbullying Detection within a Multi-Modal Context.
CoReRank: Ranking to Detect Users Involved in Blackmarket-Based Collusive Retweeting Activities.
All Those Wasted Hours: On Task Abandonment in Crowdsourcing.
Beyond News Contents: The Role of Social Context for Fake News Detection.
The Local Closure Coefficient: A New Perspective On Network Clustering.
Sampling Methods for Counting Temporal Motifs.
Attitude Detection for One-Round Conversation: Jointly Extracting Target-Polarity Pairs.
More Than Just Words: Modeling Non-Textual Characteristics of Podcasts.
Multi-Representation Fusion Network for Multi-Turn Response Selection in Retrieval-Based Chatbots.
On the Complexity of Opinions and Online Discussions.
Federated Online Learning to Rank with Evolution Strategies.
FAIRY: A Framework for Understanding Relationships Between Users' Actions and their Social Feeds.
Fighting Fire with Fire: Using Antidote Data to Improve Polarization and Fairness of Recommender Systems.
Spiral of Silence in Recommender Systems.
Protecting User Privacy: An Approach for Untraceable Web Browsing History and Unambiguous User Profiles.
Enabling Privacy-Preserving Sharing of Genomic Data for GWASs in Decentralized Networks.
Neural Based Statement Classification for Biased Language.
Uncovering Hidden Structure in Sequence Data via Threading Recurrent Models.
Social Attentional Memory Network: Modeling Aspect- and Friend-Level Differences in Recommendation.
Asynchronous Training of Word Embeddings for Large Text Corpora.
Modeling Temporal Evidence from External Collections.
RecWalk: Nearly Uncoupled Random Walks for Top-N Recommendation.
Sparsemax and Relaxed Wasserstein for Topic Sparsity.
Clustered Monotone Transforms for Rating Factorization.
A State Transition Model for Mobile Notifications via Survival Analysis.
Relevance Search over Schema-Rich Knowledge Graphs.
Knowledge Graph Embedding Based Question Answering.
Interaction Embeddings for Prediction and Explanation in Knowledge Graphs.
ExFaKT: A Framework for Explaining Facts over Knowledge Graphs and Text.
Lightweight Lexical and Semantic Evidence for Detecting Classes Among Wikipedia Articles.
CORALS: Who Are My Potential New Customers? Tapping into the Wisdom of Customers' Decisions.
Representation Interpretation with Spatial Encoding and Multimodal Analytics.
Knowledge Graph Enhanced Community Detection and Characterization.
Integrating Local Context and Global Cohesiveness for Open Information Extraction.
MSA: Jointly Detecting Drug Name and Adverse Drug Reaction Mentioning Tweets with Multi-Head Self-Attention.
WassRank: Listwise Document Ranking Using Optimal Transport Theory.
Joint Optimization of Cascade Ranking Models.
Fast Dictionary-Based Compression for Inverted Indexes.
Reinforcement Learning to Rank.
Privacy-Preserving WSDM.
Alexa Everywhere: AI for Daily Convenience.
Responsible Data Science.
Attending to What Matters.
