Integrating Deep Web Data Sources

112 p.Thesis (Ph.D.)--University of Illinois at Urbana-Champaign, 2006.This dissertation presents IceQ, a novel and effective interface integration system. In developing IceQ, we address the limitations of existing solutions and make several key contributions. First, we propose a hierarchical modeling of interfaces and develop a novel spatial clustering algorithm to extract the hierarchical schema of query interface. Second, we develop a novel interactive clustering-based matching algorithm to accurately match a large number of schemas and effectively resolve uncertain mappings via user interaction. Third, we develop a question-answering technique to learn attribute instances from the Web to assist in schema matching. Fourth, we propose a novel constraint-based optimization framework for merging schemas and develop an effective merging algorithm based on the idea of clustering aggregation. Extensive experiments have been conducted to evaluate IceQ and the results show that it is highly effective.U of I OnlyRestricted to the U of I community idenfinitely during batch ingest of legacy ETD