Establishing value mappings using statistical models and user feedback

In this paper, we present a “value mapping” algorithm that does not rely on syntactic similarity or semantic interpretation of the values. The algorithm first constructs a statistical model (e.g., co-occurrence frequency or entropy vector) that captures the unique characteristics of values and their co-occurrence. It then finds the matching values by computing the distances between the models while refining the models using user feedback through iterations. Our experimental results suggest that our approach successfully establishes value mappings even in the presence of opaque data values and thus can be a useful addition to the existing data integration techniques. Categories and Subject Descriptors H.2.5 [Database Management]: Heterogeneous Databases —Data translation General Terms Algorithms, Management Keywords Value Mapping, Semantic Correspondences, User Feedback, Statistical Model

• Type: Conference
• Year: 2005
• Where: CIKM
• Authors: Jaewoo Kang, Tae Sik Han, Dongwon Lee, Prasenjit Mitra
• Keywords: CIKM 2005, Statistical Model, User Feedback, Value Mapping