01798nas a2200133   4500008004100000245011000041210006900151260000900220520130600229100002401535700002001559700002001579856006501599       2014                        eng d00aOverlap versus partition: marketing classification and customer profiling in complex networks of products0 aOverlap versus partition marketing classification and customer p  bIEEE3 aIn recent years we witnessed the explosion in the availability of data regarding human and customer behavior in the market. This data richness era has fostered the development of useful applications in understanding how markets and the minds of the customers work. In this paper we focus on the analysis of complex networks based on customer behavior. Complex network analysis has provided a new and wide toolbox for the classic data mining task of clustering. With community discovery, i.e. the detection of functional modules in complex networks, we are now able to group together customers and products using a variety of different criteria. The aim of this paper is to explore this new analytic degree of freedom. We are interested in providing a case study uncovering the meaning of different community discovery algorithms on a network of products connected together because co-purchased by the same customers. We focus our interest in the different interpretation of a partition approach, where each product belongs to a single community, against an overlapping approach, where each product can belong to multiple communities. We found that the former is useful to improve the marketing classification of products, while the latter is able to create a collection of different customer profiles.1 aPennacchioli, Diego1 aCoscia, Michele1 aPedreschi, Dino  uhttp://ieeexplore.ieee.org/xpls/abs_all.jsp?arnumber=6818312