This repository complements our manuscript entitled 'A Local Updating Algorithm for Personalized PageRank via Chebyshev Polynomials' by Esteban Bautista and Matthieu Latapy (Submitted to Social Network Analysis and Mining).
The repository provides both the experiments reported in the paper and the code to obtain them.
Codes are written in Python.
The studied dataset is the Tech-AS-Topology.
Each experiment has its own folder which cointains the data, code, result and final figure.
The experiments are:
- Experiment 1: Performance gains of the proposed algorithm with respect to the alternative from scratch, as well as demonstration that the algorithm can update generalized PageRank vectors.
- Experiment 2: Sensitivity of the algorithm to the size of the perturbation/change in the graph
- Experiment 3: Comparison of the algorithm with state of the art alternatives
- Experiment 4: Performance of the algorithm in a tracking scenario where a PageRank vector needs to be updated during a long period of time.
Please contact esteban.bautista-ruiz@lip6.fr for any questions or problems.