Abstract
We propose a novel ranking algorithm that takes into account specific properties of the graph that represents the items and the user votes in pairwise comparison scenarios. The algorithm models the scoring relationships between instances as local edges among vertices in a corresponding graph and use such properties to find scores for each instance. We have compared the performance of the algorithm with other widely known information retrieval techniques tasked with ranking a set of movies. As a baseline implementation, we have used the topological ordering of the acyclic subgraph with maximum weight, by solving an approximated version of the maximum acyclic subgraph problem. The results show accurate ranking lists for the movie dataset.
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Notes
- 1.
Actually, any solution of a MASP instance found by using the strategy proposed in this section will not be the optimal since the removal of critical edges before building the BFS tree in step 5 changes the original problem.
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Quintero, C., Uribe, R., Calderón, J., Lozano, F. (2016). Online Pairwise Ranking Based on Graph Edge–Connectivity. In: Snášel, V., Abraham, A., Krömer, P., Pant, M., Muda, A. (eds) Innovations in Bio-Inspired Computing and Applications. Advances in Intelligent Systems and Computing, vol 424. Springer, Cham. https://doi.org/10.1007/978-3-319-28031-8_44
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