Attribute Classification Using Feature Analysis Felix Naumann, Ching-Tien Ho, Xuqing Tian, Laura Haas, and Nimrod Megiddo   View Paper (PDF)   Return to Posters Abstract The basis of many systems that integrate data from multiple sources is a set of correspondences between source schemata and a target schema. Correspondences express a relationship between sets of source attributes, possibly from multiple sources, and a set of target attributes. Clio is an integration tool that assists users in defining value correspondences between attributes. In real life scenarios there may be many sources and the source relations may have many attributes. Users can get lost and might miss or be unable to find some correspondences. Also, in many real life schemata the attribute names reveal little or nothing about the semantics of the data values. Only the data values in the attribute columns can convey the semantic meaning of the attribute. Our work relieves users of the problems of too many attributes and meaningless attribute names, by automatically suggesting correspondences between source and target attributes. For each attribute, we analyze the data values and derive a set of features DiSC'03 © 2003 Association for Computing Machinery