Functional-Dependency-Based Truth Discovery for Isomorphic Data

It is unavoidable that errors occur in databases. Reasons include recording errors, stale data, and even intentional errors. Such mistakes may cause serious consequences. It is impossible to correct those errors manually at scale. In fact, it is hard for people to even detect errors. However, since errors often occur rather randomly, they may cause inconsistencies within a database and conflicts among multiple databases from different sources. These inconsistencies and conflicts are easy to detect, but hard to repair. In this chapter, we first discuss two directions of work dealing with these inconsistencies and conflicts, namely data repairing and truth discovery. Then we introduce the idea of conducting functional-dependency-based truth discovery over multi-source data [1], which takes the advantages of both data repairing and truth discovery. Specifically, Sect. 2.1 discusses how existing methods resolve conflicts and inconsistencies and then motivates our approach. Section 2.2 defines the functional-dependency-based truth discovery problem, i.e., multi-source data repairing problem. Section 2.3 describes the overall framework and the details of each component in the framework, followed by a brief summary in Sect. 2.4.