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Intelligent Rule-Based Deep Web Crawler

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Abstract

In this chapter, architecture specification of a deep web crawler is discussed. The crawler has indexer with the capability to fetch huge documents from both surface and deep web. The documents from the deep web are fetched-based rules, where core and allied fields of the forms play important role. Based on the domain and nature of FORM in HTML pages, functional dependency between the fields, core and allied fields are identified. The SVM classifier is used for classifying the rule as most preferable, least preferable and mutually exclusive. The documents are fetched by using the most preferable fields in FORM. The fetched document is indexed, and the same architecture is scaled to support distributed functionality with the help of web services. This architecture specification processes huge number of documents which has encouraging coverage rate and lower fetching time. The retrieval performance of the crawler is compared with Google retrieval system and found that the proposed architecture archives similar procession of retrieval.

Keywords

Deep web crawler Indexer Rules Hidden web data 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.Department of Computer Science and EngineeringDayananda Sagar UniversityBangaloreIndia
  2. 2.Department of Computer Science and EngineeringSRM University APAmaravatiIndia

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