Quality-Aware Retrieval of Data Objects from Autonomous Sources for Web-Based Repositories

The goal of this paper is to develop a framework for designing good data repositories for Web applications. The central theme of our approach is to employ statistical methods to predict quality metrics. These prediction quantities can be used to answer important questions such as: How soon should the local repository be synchronized to have a quality of at least 90% precision with certain confidence level? Suppose the local repository was synchronized three days ago, how many objects could have been deleted at the remote source since then?