Association for Computing Machinery
In this paper, the authors concentrate on categorization of relational attributes based on their data type. Assuming that attribute type/characteristics are unknown or unidentifiable, they analyze and compare a variety of type-based signatures for classifying the attributes based on the semantic type of the data contained therein (e.g., router identifiers, social security numbers, email addresses). The signatures can subsequently be used for other applications as well, like clustering and index optimization/compression. This application is useful in cases where very large data collections that are generated in a distributed, ungoverned fashion end up having unknown, incomplete, inconsistent or very complex schemata and schema level meta-data.