Inferring data currency and consistency for conflict resolution

Wenfei Fan, Floris Geerts, Nan Tang, Wenyuan Yu

Research output: Chapter in Book/Report/Conference proceedingConference contribution

Abstract / Description of output

This paper introduces a new approach for conflict resolution: given a set of tuples pertaining to the same entity, it is to identify a single tuple in which each attribute has the latest and consistent value in the set. This problem is important in data integration, data cleaning and query answering. It is, however, challenging since in practice, reliable timestamps are often absent, among other things. We propose a model for conflict resolution, by specifying data currency in terms of partial currency orders and currency constraints, and by enforcing data consistency with constant conditional functional dependencies. We show that identifying data currency orders helps us repair inconsistent data, and vice versa. We investigate a number of fundamental problems associated with conflict resolution, and establish their complexity. In addition, we introduce a framework and develop algorithms for conflict resolution, by integrating data currency and consistency inferences into a single process, and by interacting with users. We experimentally verify the accuracy and efficiency of our methods using real-life and synthetic data.
Original languageEnglish
Title of host publication29th IEEE International Conference on Data Engineering, ICDE 2013, Brisbane, Australia, April 8-12, 2013
PublisherInstitute of Electrical and Electronics Engineers (IEEE)
Number of pages12
ISBN (Electronic)978-1-4673-4908-6
ISBN (Print)978-1-4673-4909-3
Publication statusPublished - Apr 2013


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