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Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted and undirected graph. It is based on a Markov-chain modelExpand
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Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure
It sometimes happens (for instance in case control studies) that a classifier is trained on a data set that does not reflect the true a priori probabilities of the target classes on real-world data.Expand
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An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification
This paper presents a survey as well as an empirical comparison and evaluation of seven kernels on graphs and two related similarity matrices, that we globally refer to as "kernels on graphs" forExpand
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The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering
This work presents a novel procedure for computing (1) distances between nodes of a weighted, undirected, graph, called the Euclidean Commute Time Distance (ECTD), and (2) a subspace projection ofExpand
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An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task
This work presents a systematic comparison between seven kernels (or similarity matrices) on a graph, namely the exponential diffusion kernel, the Laplacian diffusion kernel, the von Neumann kernel,Expand
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Randomized Shortest-Path Problems: Two Related Models
This letter addresses the problem of designing the transition probabilities of a finite Markov chain (the policy) in order to minimize the expected cost for reaching a destination node from a sourceExpand
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The Sum-over-Paths Covariance Kernel: A Novel Covariance Measure between Nodes of a Directed Graph
This work introduces a link-based covariance measure between the nodes of a weighted directed graph, where a cost is associated with each arc. To this end, a probability distribution on the (usuallyExpand
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A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances
This work introduces a new family of link-based dissimilarity measures between nodes of a weighted directed graph. This measure, called the randomized shortest-path (RSP) dissimilarity, depends on aExpand
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Evaluating Performance of Recommender Systems: An Experimental Comparison
Much early evaluation work focused specifically on the "accuracy" of recommendation algorithms. Good recommendation (in terms of accuracy) has, however, to be coupled with other considerations. ThisExpand
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A Novel Way of Computing Dissimilarities between Nodes of a Graph, with Application to Collaborative Filtering
This work presents a new perspective on characterizing the similarity between elements of a database or, more generally, nodes of a weighted, undirected, graph. It is based on a Markov-chain model ofExpand
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