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A Novel Meta Crawling Algorithm for Terrorist Network Knowledge Aggregation from the Internet

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Smart Computing and Informatics

Part of the book series: Smart Innovation, Systems and Technologies ((SIST,volume 77))

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Abstract

Nowadays, World Wide Web is flooded with different types of web browsers. Each of these web browsers differs from one another on the basis of search time, search efficiency and the area of the Internet they cover in their search. The popular search engines like Yahoo Search, Google, Dogpile, Bing, Ask, etc., are facing efficiency challenges due to tremendous growth rate of data on the Internet. Moreover, the current state of the art in this field works on the general search results. Hence, special data mining search results require customized search services. Terrorist network mining is one such field of data mining which requires customized search services. This paper presents the algorithm for customized Terrorist Meta Crawler. The algorithm presented in this paper is optimized to search terrorist-related information on World Wide Web using different web services. The last section of this paper presents the comparative effectiveness of Terrorist Meta Crawler along with other popular search engines, and results show Terrorist Meta Crawler is a better solution for customized search.

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References

  1. Gaharwar, R.D., Shah, D.B.: Architectural design of Meta Crawler for Terrorist Network Mining. Commun. Appl. Electron. 5(8), 37–40 (2016)

    Article  Google Scholar 

  2. Etzioni, O.: Moving up the information food chain: deploying softbots on the world wide web. AI Mag. 18(2), 11 (1997)

    Google Scholar 

  3. Gaharwar, R.D., Shah, D.B., Gaharwar, G.K.S.: The study of multi-search services for Terrorist Network Mining. Commun. Appl. Electron. 5(8), 37–40 (2016)

    Article  Google Scholar 

  4. Links & Law: Information about legal aspects of search engines, linking and framing. http://www.linksandlaw.com/technicalbackground-search-engine-spamming.htm

  5. Yang, X., Zhang, M.: Necessary constraints for fusion algorithms in meta search engine systems. In: Proceedings of the International Conference on Intelligent Technologies, pp. 409–416 (2000)

    Google Scholar 

  6. Selberg, E., Etzioni, O.: Multi-service search and comparison using the MetaCrawler. In: Proceedings of the Fourth International WWW Conference, Boston (1995)

    Google Scholar 

  7. Laria, V.G., Griffiths, R., Winstanley, G.: Application of a clustering algorithm to recover topic content in an unstructured text-based environment. https://www.researchgate.net/profile/Graham_Winstanley/publication/2504349_Application_of_a_Clustering_Algorithm_to_Recover_Topic_Content_in_an_Unstructured_TextBased_Environment/links/02e7e52f231abb5cac000000.pdf

  8. Selberg, E., Etzioni, O.: The MetaCrawler architecture for resource aggregation on the Web. IEEE Expert 12(1), 11–14 (1997)

    Article  Google Scholar 

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Authors and Affiliations

  1. G H Patel Post Graduate Department of Computer Science and Technology, Sardar Patel University, Vallabh Vidyanagar, India

    R. D. Gaharwar & D. B. Shah

Authors
  1. R. D. Gaharwar
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  2. D. B. Shah
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Corresponding author

Correspondence to R. D. Gaharwar .

Editor information

Editors and Affiliations

  1. Department of Computer Science and Engineering, PVP Siddhartha Institute of Technology, Vijayawada, Andhra Pradesh, India

    Suresh Chandra Satapathy

  2. Department of Electronics and Communication Engineering, Shri Ramswaroop Memorial Group of Professional Colleges, Lucknow, Uttar Pradesh, India

    Vikrant Bhateja

  3. Electronics and Communication Sciences Unit, Indian Statistical Institute, Kolkata, West Bengal, India

    Swagatam Das

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© 2018 Springer Nature Singapore Pte Ltd.

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Gaharwar, R.D., Shah, D.B. (2018). A Novel Meta Crawling Algorithm for Terrorist Network Knowledge Aggregation from the Internet. In: Satapathy, S., Bhateja, V., Das, S. (eds) Smart Computing and Informatics . Smart Innovation, Systems and Technologies, vol 77. Springer, Singapore. https://doi.org/10.1007/978-981-10-5544-7_36

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  • DOI: https://doi.org/10.1007/978-981-10-5544-7_36

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-5543-0

  • Online ISBN: 978-981-10-5544-7

  • eBook Packages: EngineeringEngineering (R0)

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