Reference Reconciliation in Complex Information Spaces

Reference reconciliation is the problem of identifying when different references (i.e., sets of attribute values) in a dataset correspond to the same real-world entity. Most previous literature assumed references to a single class that had a fair number of attributes (e.g., research publications). We consider complex information spaces: our references belong to multiple related classes and each reference may have very few attribute values. A prime example of such a space is Personal Information Management, where the goal is to provide a coherent view of all the information on one's desktop. Our reconciliation algorithm has three principal features. First, we exploit the associations between references to design new methods for reference comparison. Second, we propagate information between reconciliation decisions to accumulate positive and negative evidences. Third, we gradually enrich references by merging attribute values. Our experiments show that (1) we considerably improve p...

• Type: Conference
• Year: 2005
• Where: SIGMOD
• Authors: Xin Dong, Alon Y. Halevy, Jayant Madhavan
• Keywords: Attribute Values, Database, Literature Assumed References, SIGMOD 2005, Standard Citation Dataset