Semantic Integration in Heterogeneous Databases Using Neural Networks

One important step in integrating heterogeneous databases is matching equivalent attributes: Determining which fields in two databasesrefer to the samedata. The meaning of information may be embodied within a. database model, a conceptual schema, application programs, or data contents. Integration involves extracting semantics, expressing them asmetadata, and matching semantically equivalent data elements. We present a procedure using a classifier to categorizeattributes according to their field specifications and data values, then train a neural network to recognize similar attributes. In our technique, the knowledge of how to match equivalent data elements is "discovered" from metadata , not "pre-programmed".

• Type: Conference
• Year: 1994
• Where: VLDB
• Authors: Wen-Syan Li, Chris Clifton
• Keywords: Database, Equivalent Attributes, Equivalent Data Elements, Heterogeneous Databases, VLDB 1994