Overview of the relational analysis approach in data-mining and multi-criteria decision making

Julien Ah-Pine , Jean-François Marcotorchino (1)

1 THALES [France]

In this chapter we introduce a general framework called the Relational Analysis approach and its related contributions and applications in the fields of data analysis, data mining and multi-criteria decision making. This approach was initiated by J.F. Marcotorchino and P. Michaud at the end of the 70's and has generated many research activities. However, the aspects of this framework that we would like to focus on are of a theoretical kind. Indeed, we are aimed at recalling the background and the basics of this framework, the unifying results and the modeling contributions that it has allowed to achieve. Besides, the main tasks that we are interested in are the ranking aggregation problem, the clustering problem and the block seriation problem. Those problems are combinatorial ones and the computational considerations of such tasks in the context of the RA methodology will not be covered. However, among the list of references that we give thoughout this chapter, there are numerous articles that the interested reader could consult to this end.

Domaines: Machine Learning [stat.ML]; Apprentissage [cs.LG]; Recherche opérationnelle [math.OC]

Julien Ah-Pine, Jean-François Marcotorchino. Overview of the relational analysis approach in data-mining and multi-criteria decision making. Zeeshan-Ul-Hassan Usmani. Web Intelligence and Intelligent Agents, Intech, pp.325-346, 2010, 978-953-7619-85-5. ⟨10.5772/8387⟩. ⟨hal-01504568⟩