Well-organized association Pattern Mining using Multi-relational Data Cubes
A large class of data mining applications involves data sets that pertain to multiple entities and relationship. This has led to the suggestion of Multi-Relational Data Mining (MRDM) that aims to incorporate and exploit the heterogeneous and semantically rich relationships that exist among entity types. Specially, given a database consisting of multiple tables linked through foreign key joins, a target table (that typically represents a certain real-world entity type) and, optionally, a target attribute (e.g. a class label attribute), MRDM aims to discover patterns and models spanning all the tables and links that either describe or predict the target entity or attribute.