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Found 6 papers, 4 papers with code
Pure Spectral Graph Embeddings: Reinterpreting Graph Convolution for Top-N Recommendation
The use of graph convolution in the development of recommender system algorithms has recently achieved state-of-the-art results in the collaborative filtering task (CF).
Item Graph Convolution Collaborative Filtering for Inductive Recommendations
We propose the construction of an item-item graph through a weighted projection of the bipartite interaction network and to employ convolution to inject higher order associations into item embeddings, while constructing user representations as weighted sums of the items with which they have interacted.
Inferring Hierarchical Mixture Structures: A Bayesian Nonparametric Approach
This paper focuses on the problem of hierarchical non-overlapping clustering of a dataset.
Story Disambiguation: Tracking Evolving News Stories across News and Social Streams
This is particularly the case for local news stories that are easily over shadowed by other trending stories, and for complex news stories with ambiguous content in noisy stream environments.
Percolation Computation in Complex Networks
We motivate a simple algorithm to conduct clique percolation, and investigate its performance compared to current best-in-class algorithms.
Social and Information Networks Physics and Society
Normalized Mutual Information to evaluate overlapping community finding algorithms
Given the increasing popularity of algorithms for overlapping clustering, in particular in social network analysis, quantitative measures are needed to measure the accuracy of a method.
Physics and Society Social and Information Networks Data Analysis, Statistics and Probability
