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Learning-To-Rank

Learning to rank is the application of machine learning to build ranking models. Some common use cases for ranking models are information retrieval (e.g., web search) and news feeds application (think Twitter, Facebook, Instagram).

Papers

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Showing 501–525 of 753 papers

TitleStatusHype
ViTOR: Learning to Rank Webpages Based on Visual Features—0
On Application of Learning to Rank for E-Commerce Search—0
Exploiting Unlabeled Data in CNNs by Self-supervised Learning to RankCode0
A Domain Generalization Perspective on Listwise Context Modeling—0
Policy Learning for Fairness in RankingCode0
Joint Optimization of Cascade Ranking ModelsCode0
Optimizing Ranking Models in an Online Setting—0
Neural IR Meets Graph Embedding: A Ranking Model for Product Search—0
Opportunistic Learning: Budgeted Cost-Sensitive Learning from Data StreamsCode0
Position Bias Estimation for Unbiased Learning-to-Rank in eCommerce Search—0
Factorization Machines for Data with Implicit Feedback—0
Estimating Position Bias without Intrusive Interventions—0
Top-N-Rank: A Scalable List-wise Ranking Method for Recommender Systems—0
A Knowledge Graph Based Solution for Entity Discovery and Linking in Open-Domain Questions—0
MOFSRank: A Multiobjective Evolutionary Algorithm for Feature Selection in Learning to Rank—0
TF-Ranking: Scalable TensorFlow Library for Learning-to-RankCode0
Intervention Harvesting for Context-Dependent Examination-Bias Estimation—0
Learning to Rank Query Graphs for Complex Question Answering over Knowledge GraphsCode0
Online Diverse Learning to Rank from Partial-Click Feedback—0
Ontology-Based Retrieval \& Neural Approaches for BioASQ Ideal Answer Generation—0
Retrieve and Re-rank: A Simple and Effective IR Approach to Simple Question Answering over Knowledge Graphs—0
Online Learning to Rank with Features—0
Entity Linking within a Social Media Platform: A Case Study on YelpCode0
Understanding the Gist of Images - Ranking of Concepts for Multimedia Indexing—0
Query Understanding via Entity Attribute Identification—0
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