Deep Web Information Retrieval Process-Reference-Cited by-同舟云学术

Deep Web Information Retrieval Process

Published:2018 Issue: Volume: Page:114-137
ISSN:
Container-title:The Dark Web
language:
Short-container-title:

Author:

Sharma Dilip Kumar¹,Sharma A. K.²

Affiliation:

1. G.L.A. Institute of Technology and Management, Mathura, India

2. YMCA University of Science and Technology, Faridabad, India

Abstract

Web crawlers specialize in downloading web content and analyzing and indexing from surface web, consisting of interlinked HTML pages. Web crawlers have limitations if the data is behind the query interface. Response depends on the querying party's context in order to engage in dialogue and negotiate for the information. In this paper, the authors discuss deep web searching techniques. A survey of technical literature on deep web searching contributes to the development of a general framework. Existing frameworks and mechanisms of present web crawlers are taxonomically classified into four steps and analyzed to find limitations in searching the deep web.

Publisher

IGI Global

Reference53 articles.

1. Akilandeswari, J., & Gopalan, N. P. (2008). An Architectural Framework of a Crawler for Locating Deep Web Repositories Using Learning Multi-agent Systems. In Proceedings of the 2008 Third International Conference on Internet and Web Applications and Services (pp.558-562).

2. ANSI/NISO Z39. 50. (2003). Information Retrieval: Application Service Definition and Protocol Specification. Retrieved from http://www.niso.org/standards/standard_detail.cfm?std_id=465.

3. Arlotta, L., Crescenzi, V., Mecca, G., et al. (2003). Automatic annotation of data extracted from large Web sites. In Proceedings of the 6th International Workshop on Web and Databases, San Diego, CA (pp. 7-12).

4. A Framework for Domain Specific Interface Mapper (DSIM).;K. K.Bhatia;International Journal of Computer Science and Network Security,2008

5. BrightPlanet.com LLC. (2000, July). White Paper: The Deep Web: Surfacing Hidden Value.