Papers Collaborative Filtering
“Collaborative Filtering” 태그가 달린 논문 1,408편 · 필터 해제
Matrix Completion from Noisy Entries
Given a matrix M of low-rank, we consider the problem of reconstructing it from noisy observations of a small, random subset of its entries. The problem arises in a variety of applications, from collaborative filtering (…
Collaborative FilteringMatrix CompletionStochastic Relational Models for Large-scale Dyadic Data using MCMC
Stochastic relational models provide a rich family of choices for learning and predicting dyadic data between two sets of entities. It generalizes matrix factorization to a supervised learning problem that utilizes attri…
Bayesian InferenceCollaborative FilteringOn quantum statistics in data analysis
Originally, quantum probability theory was developed to analyze statistical phenomena in quantum systems, where classical probability theory does not apply, because the lattice of measurable sets is not necessarily distr…
Collaborative FilteringInformation RetrievalRetrievalEmpirical Evaluation of Four Tensor Decomposition Algorithms
Higher-order tensor decompositions are analogous to the familiar Singular Value Decomposition (SVD), but they transcend the limitations of matrices (second-order tensors). SVD is a powerful tool that has achieved impress…
Collaborative FilteringInformation RetrievalRetrievalTensor DecompositionRestricted Boltzmann Machines for Collaborative Filtering
Most of the existing approaches to collaborative filtering cannot handle very large data sets. In this paper we show how a class of two-layer undirected graphical models, called Restricted Boltzmann Machines (RBM's), can…
Collaborative FilteringRecommendation SystemsRecommender System for Online Dating Service
Users of online dating sites are facing information overload that requires them to manually construct queries and browse huge amount of matching user profiles. This becomes even more problematic for multimedia profiles. …
Collaborative FilteringRecommendation SystemsSlope One Predictors for Online Rating-Based Collaborative Filtering
Rating-based collaborative filtering is the process of predicting how a user would rate a given item from other user ratings. We propose three related slope one schemes with predictors of the form f(x) = x + b, which pre…
Collaborative FilteringLatent Dirichlet Allocation
We describe latent Dirichlet allocation (LDA), a generative probabilistic model for collections of discrete data such as text corpora. LDA is a three-level hierarchical Bayesian model, in which each item of a collectio…
Collaborative Filteringparameter estimationText Categorizationtext-classification+2