Confidence on Approximate Query in Large Datasets

  • Authors:
  • Charles Wesley Ford;Chia-Chu Chiang;Hao Wu;Radhika R. Chilka;John Talburt

  • Affiliations:
  • -;-;-;-;-

  • Venue:
  • ITCC '04 Proceedings of the International Conference on Information Technology: Coding and Computing (ITCC'04) Volume 2 - Volume 2
  • Year:
  • 2004

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Abstract

The evolution of the World Wide Web has brought usenormous amounts of information for business and researchuse. Design and implementation of an automatedsystem for web data mining has become important for companieswishing to utilize useful information from the web.This paper is an attempt at describing confidence on approximatequeries on large datasets which is done in thecontext of an automated system for web data mining. Thesystem has been designed to identify, extract, filter, andanalyze data from web resources. An approach to evaluatingthe quality of extracted web data is also discussed. Thiswork is an exploratory study of web data retrieval and webdata analysis.