Abstract
A number of important decisions are based on a set of specific items in a database called the select items. Thus the analysis of select items in multiple databases becomes of primordial relevance. In this chapter, we focus on the following issues. First, a model of mining global patterns of select items from multiple databases is presented. Second, a measure of quantifying an overall association between two items in a database is discussed. Third, we present an algorithm that is based on the proposed overall association between two items in a database for the purpose of grouping the frequent items in multiple databases. Each group contains a select item called the nucleus item and the group grows while being centered around the nucleus item. Experimental results are concerned with some synthetic and real-world databases.
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Adhikari, A., Ramachandrarao, P., Pedrycz, W. (2010). Mining Patterns of Select Items in Multiple Databases. In: Developing Multi-Database Mining Applications. Advanced Information and Knowledge Processing. Springer, London. https://doi.org/10.1007/978-1-84996-044-1_4
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DOI: https://doi.org/10.1007/978-1-84996-044-1_4
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