1-semantic deep web-automatic attribute extraction from theVIP

Semantic Deep Web: Automatic Attribute Extraction from the Deep Web Data Sources YOO JUNG AN JAMES GELLER YI-TA WU SOON AE CHUN Department of Computer Department of Computer Department of Department of Business Science, Science, Radiology CUNY, College of New Jersey Institute of New Jersey Institute of University of Michigan, Staten Island, Staten Technology, Newark, Technology, Newark, Ann Arbor, MI 48105 Island, NY 10314 NJ 07102 NJ 07102 +1 973 517 6219 +1 718 982 2981 +1 973 596 2867 +1 973 596 3383 yitawu@ chun@mail.csi.cuny ya8@ geller@ .edu ABSTRACT The challenge is then to identify the Web query interface “Deep Web” refers to the rich information and data hidden in pages that may “reveal” Web data sources of hidden contents backend databases, etc., that search engines or Web crawlers most relevant to the user’s search keywords (i.e. user’s interests). cannot access. It is mostly accessible through manual query To this end, Kabra et al. [5] proposed an attribute relevance model interfaces. This paper introduces the