Danubianu M. (2017) Data Mining - A Tool for Migration Stock Prediction. In: Kozielski S., Mrozek D., Kasprowski P., Małysiak-Mrozek B., Kostrzewa D. (eds) Beyond Databases, Architectures and Structures. Towards Efficient Solutions for Data Analysis and Knowledge Representation. BDAS 2017. Communications in Computer and Information Science, vol 716. Springer, Cham
The migration phenomenon is an important issue for most of the European Unions countries and it has a major socio-economic impact for all parts involved. After 1989, a massive migration process started to develop from Romania towards Western European countries. Beside qualified personnel in search of different and new opportunities, Roma people became more visible, as they were emigrating in countries with high living standards where they were generating significant integration problems along with costs. In order to identify the problems faced by the Roma community from Rennes, a group of sociologists developed a questionnaire, which contains, among other questions, one relating to the intention of returning home. This paper presents a research that aims to build various models, by data mining techniques, to predict that Roma people return to the home country after a five years interval. The second goal is to assess these models and to identify those aspects that have most influence in the decision-making process. The result is based on the data completed by more than 100 persons from Rennes.
Data mining Classification CRISP-DM model Migration phenomenon Return prediction