Architectures for Deep Web Data Extraction and Integration

Deep Web, as a rich and largely unexplored data source, is becoming nowadays an important research topic. In previous years, data extraction from Web pages has received a lot of attention. Much experience has been also already accumulated in the area of traditional, relational databases integration. Today, these research areas converge, leading to development of systems for Deep Web data extraction and integration. Several approaches were proposed and many systems were built that enable extraction and integration of Deep Web data. In the paper we propose a classification framework allowing to compare different approaches based on the full model of data extraction and integration process. We classify the most important systems reported in the literature according to the proposed framework; they are evaluated with respect to their capabilities and coverage of the process. We conclude with the refinement of the architecture that would cover the complete data extraction and integration process for Web sources.