Genetic algorithm-based intelligent multiagent architecture for extracting information from hidden web databases Online publication date: Thu, 30-Jan-2020
by D. Weslin; T. Joshva Devadas
International Journal of Business Intelligence and Data Mining (IJBIDM), Vol. 16, No. 2, 2020
Abstract: Though there are enormous amount of information available in the web, only very small portion of the available information is visible to the users. Due to the non-visibility of huge information, the traditional search engines cannot index or access all information present in the web. The main challenge in the mining of the relevant information from a huge hidden web database is to identify the entry points to access the hidden web databases. The existing web crawlers cannot retrieve all information from the hidden web databases. To retrieve all the relevant information from the hidden web, this paper proposes an architecture that uses genetic algorithm and intelligent agents for accessing hidden web databases. The proposed architecture is termed as genetic algorithm-based intelligent multi-agent system (GABIAS). The experimental results show that the proposed architecture provides better precision and recall than the existing web crawlers.
Existing subscribers:
Go to Inderscience Online Journals to access the Full Text of this article.
If you are not a subscriber and you just want to read the full contents of this article, buy online access here.Complimentary Subscribers, Editors or Members of the Editorial Board of the International Journal of Business Intelligence and Data Mining (IJBIDM):
Login with your Inderscience username and password:
Want to subscribe?
A subscription gives you complete access to all articles in the current issue, as well as to all articles in the previous three years (where applicable). See our Orders page to subscribe.
If you still need assistance, please email subs@inderscience.com
Our Blog 
Follow us on Twitter 
Visit us on Facebook