Extraction and integration of partially overlapping web sources

We present an unsupervised approach for harvesting the data ex-posed by a set of structured and partially overlapping data-intensive web sources. Our proposal comes within a formal framework tack-ling two problems: the data extraction problem, to generate ex-traction rules based on the input websites, and the data integration problem, to integrate the extracted data in a unified schema. We introduce an original algorithm, WEIR, to solve the stated problems and formally prove its correctness. WEIR leverages the overlap-ping data among sources to make better decisions both in the data extraction (by pruning rules that do not lead to redundant informa-tion) and in the data integration (by reflecting local properties of a source over the mediated schema). Along the way, we characterize the amount of redundancy needed by our algorithm to produce a solution, and present experimental results to show the benefits of our approach with respect to existing solutions. 1