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Pelleg, D. and Moore, A.W. (2000) X-Means: Extending K-Means with Efficient Estimation of the Number of Clusters. Proceedings of the Seventeenth International Conference on Machine Learning (ICML 2000), Stanford, 29 June 2000-2 July 2000, 727-734.

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• TITLE: Data Integration Techniques for the Construction of an Integrated Database on the Economic Sustainability of Italian Families

  AUTHORS: Samuela L’Abbate, Paola Perchinunno, Antonella Massari, Corrado Crocetta, Leonardo Salvatore Alaimo

  KEYWORDS: Statistical Matching, Data Integration Techniques, Record Linkage

  JOURNAL NAME: Applied Mathematics, Vol.16 No.11, November 24, 2025

  ABSTRACT: This work describes a data integration model using the Statistical Matching methodology (hot deck distance) to integrate two surveys conducted by ISTAT (EU-SILC) and the Bank of Italy (Household Income Survey). The construction of an integrated database based on these surveys is useful for studying consumer behavior in relation to specific commodity groups, analyzing household savings decisions, assessing economic and social inequality, and evaluating the impact of public policies through simulations. The coexistence of multiple and diverse objectives necessitates a highly general and versatile integrated file, providing detailed information on spending patterns, savings levels, income distribution, occupational conditions of household members, and more.