Probe. Cluster, and Discover: Focused Extraction of QA-Pagelets from the Deep Web
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In this paper, we introduce the concept of a QA-Pagelet to refer to the content region in a dynamic page that contains query matches. We present THOR, a scalable and efficient mining system for discovering and extracting QA-Pagelets from the Deep Web. A unique feature of THOR is its two-phase extraction framework. In the first phase, pages from a deep web site are grouped into distinct clusters of structurally-similar pages. In the second phase, pages from each page cluster are examined through a subtree filtering algorithm that exploits the structural and content similarity at subtree level to identify the QA-Pagelets.
author list (cited authors)
Caverlee, J., Liu, L., & Buttler, D.
editor list (cited editors)
Özsoyoglu, Z. M., & Zdonik, S. B.