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- Publications
- Influence

Random-Walk Computation of Similarities between Nodes of a Graph with Application to Collaborative Recommendation

- François Fouss, A. Pirotte, Jean-Michel Renders, Marco Saerens
- Computer Science
- IEEE Transactions on Knowledge and Data…
- 1 March 2007

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 model… Expand

Adjusting the Outputs of a Classifier to New a Priori Probabilities: A Simple Procedure

- Marco Saerens, Patrice Latinne, C. Decaestecker
- Computer Science, Medicine
- Neural Computation
- 2002

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

An experimental investigation of kernels on graphs for collaborative recommendation and semisupervised classification

- François Fouss, Kevin Françoisse, Luh Yen, A. Pirotte, Marco Saerens
- Medicine, Computer Science
- Neural Networks
- 1 July 2012

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" for… Expand

The Principal Components Analysis of a Graph, and Its Relationships to Spectral Clustering

- Marco Saerens, François Fouss, Luh Yen, P. Dupont
- Mathematics, Computer Science
- ECML
- 20 September 2004

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 of… Expand

An Experimental Investigation of Graph Kernels on a Collaborative Recommendation Task

- François Fouss, Luh Yen, A. Pirotte, Marco Saerens
- Computer Science
- Sixth International Conference on Data Mining…
- 18 December 2006

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

Randomized Shortest-Path Problems: Two Related Models

- Marco Saerens, Youssef Achbany, François Fouss, Luh Yen
- Medicine, Computer Science
- Neural Computation
- 1 August 2009

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 source… Expand

The Sum-over-Paths Covariance Kernel: A Novel Covariance Measure between Nodes of a Directed Graph

- A. Mantrach, Luh Yen, Jérôme Callut, Kevin Françoisse, M. Shimbo, Marco Saerens
- Medicine, Mathematics
- IEEE Transactions on Pattern Analysis and Machine…
- 1 June 2010

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 (usually… Expand

A family of dissimilarity measures between nodes generalizing both the shortest-path and the commute-time distances

- Luh Yen, Marco Saerens, A. Mantrach, M. Shimbo
- Mathematics, Computer Science
- KDD
- 24 August 2008

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 a… Expand

Evaluating Performance of Recommender Systems: An Experimental Comparison

- François Fouss, Marco Saerens
- Computer Science
- IEEE/WIC/ACM International Conference on Web…
- 9 December 2008

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. This… Expand

A Novel Way of Computing Dissimilarities between Nodes of a Graph, with Application to Collaborative Filtering

- François Fouss, A. Pirotte, Marco Saerens
- Mathematics, Computer Science
- 2004

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 of… Expand

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