Structure based Data Extraction from Hidden Web Sources: A Review | Zendy

Author Anuradha | Zendy; Anukrati Sharma | Zendy

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Structure based Data Extraction from Hidden Web Sources: A Review

Author(s) -

Author Anuradha,

Anukrati Sharma

Publication year - 2011

Publication title -

international journal of computer applications

Language(s) - English

Resource type - Journals

ISSN - 0975-8887

DOI - 10.5120/3010-4060

Subject(s) - computer science , data extraction , extraction (chemistry) , information retrieval , data science , data mining , world wide web , medline , chromatography , political science , law , chemistry

order to extract data from the web pages of Hidden web sources, many semiautomatic and automatic techniqu es are proposed based on structure and tags of HTML documents. These techniques include machine learning and schemamat ching approaches to solve the problem of data extraction. This paper discusses the research that has been done in the area of data extraction from Hidden Web sources. The goal of this paper is to discuss the advantages and disadvantages of currently existing techniques.

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