Characterizing and selecting fresh data sources
Theodoros Rekatsinas, Xin Luna Dong, Divesh Srivastava · 2014
Data integration is a challenging task due to the large numbers of autonomous data sources. This necessitates the development of techniques to reason about the benefits and costs of acquiring and integrating data. Recently the problem of source selection (i.e., identifying the subset of sources that maximizes the profit from integration) was introduced as a preprocessing step before the actual integration. The problem was studied for static sources and used the accuracy of data fusion to quantify the integration profit.