Online Data Fusion
The Web contains a significant volume of structured data in various domains, but a lot of data are dirty and erroneous, and they can be propagated through copying. While data integration techniques allow querying structured data on the Web, they take the union of the answers retrieved from different sources and can thus return conflicting information. Data fusion techniques, on the other hand, aim to find the true values, but are designed for offline data aggregation and can take a long time. This paper proposes SOLARIS, the first online data fusion system. It starts with returning answers from the first probed source, and refreshes the answers as it probes more sources and applies fusion techniques on the retrieved data.