Understanding deep web search interfaces: a survey

  • Authors:

  • Ritu Khare;Yuan An;Il-Yeol Song

  • Affiliations:

  • Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA;Drexel University, Philadelphia, PA, USA

  • Venue:
  • ACM SIGMOD Record
  • Year:
  • 2010

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Abstract

This paper presents a survey on the major approaches to search interface understanding. The Deep Web consists of data that exist on the Web but are inaccessible via text search engines. The traditional way to access these data, i.e., by manually filling-up HTML forms on search interfaces, is not scalable given the growing size of Deep Web. Automatic access to these data requires an automatic understanding of search interfaces. While it is easy for a human to perceive an interface, machine processing of an interface is challenging. During the last decade, several works addressed the automatic interface understanding problem while employing a variety of understanding strategies. This paper presents a survey conducted on the key works. This is the first survey in the field of search interface understanding. Through an exhaustive analysis, we organize the works on a 2-D graph based on the underlying database information extracted and based on the technique employed.