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Found 10 papers, 1 papers with code
SAGE: Structured Attribute Value Generation for Billion-Scale Product Catalogs
We introduce SAGE; a Generative LLM for inferring attribute values for products across world-wide e-Commerce catalogs.
Trust your neighbors: A comprehensive survey of neighborhood-based methods for recommender systems
Collaborative recommendation approaches based on nearest-neighbors are still highly popular today due to their simplicity, their efficiency, and their ability to produce accurate and personalized recommendations.
Projection techniques to update the truncated SVD of evolving matrices
This paper considers the problem of updating the rank-k truncated Singular Value Decomposition (SVD) of matrices subject to the addition of new rows and/or columns over time.
Random Surfing Revisited: Generalizing PageRank's Teleportation Model
We revisit the Random Surfer model, focusing on its--often overlooked--Teleportation component, and we introduce NCDawareRank; a novel ranking framework designed to exploit network meta-information as well as aspects of its higher-order structural organization in a way that preserves the mathematical structure and the attractive computational characteristics of PageRank.
Boosting Item-based Collaborative Filtering via Nearly Uncoupled Random Walks
Item-based models are among the most popular collaborative filtering approaches for building recommender systems.
Adaptive Diffusions for Scalable Learning over Graphs
Diffusion-based classifiers such as those relying on the Personalized PageRank and the Heat kernel, enjoy remarkable classification accuracy at modest computational requirements.
Kernel-based Inference of Functions over Graphs
The study of networks has witnessed an explosive growth over the past decades with several ground-breaking methods introduced.
EigenRec: Generalizing PureSVD for Effective and Efficient Top-N Recommendations
We introduce EigenRec; a versatile and efficient Latent-Factor framework for Top-N Recommendations that includes the well-known PureSVD algorithm as a special case.
Top-N recommendations in the presence of sparsity: An NCD-based approach
Making recommendations in the presence of sparsity is known to present one of the most challenging problems faced by collaborative filtering methods.
Random Surfing Without Teleportation
In the standard Random Surfer Model, the teleportation matrix is necessary to ensure that the final PageRank vector is well-defined.
