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Artificial Intelligence and Evolutionary Algorithms in Engineering Systems pp 1–8Cite as

Web Information Extraction on Multiple Ontologies Based on Concept Relationships upon Training the User Profiles

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Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 325))

Abstract

There is a need of personalized Web information extraction. Mining vast information across the Web is not an easy task. We need to undergo various reduction techniques to remove unwanted data and to grab the useful information from the Web resources. Ontology is the best way for representing the useful information. In this paper, we have planned to develop a model based on multiple ontologies. From the constructed ontologies based on the mutual information among the concepts the taxonomy is constructed, then the relationship among the concepts is calculated. Thereby, the useful information is extracted. An algorithm is proposed for the same. The results show that the computation time for data extraction is reduced as the size of the database increases. This shows a healthy improvement for quick access of useful data from a huge information resource like the Internet.

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Author information

Authors and Affiliations

  1. Department of Computer Science and Engineering, Sathyabama University, Chennai, India

    S. Vigneshwari

  2. Perunthalaivar Kamarajar Institute of Engineering and Technology, Karaikal, Tamil Nadu, India

    M. Aramudhan

Authors
  1. S. Vigneshwari
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  2. M. Aramudhan
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Corresponding author

Correspondence to S. Vigneshwari .

Editor information

Editors and Affiliations

  1. Electrical & Electronics Engineering, Noorul Islam Centre for Higher Education, Kumaracoil, Tamil Nadu, India

    L Padma Suresh

  2. Electrical and Electronics Engineering, SRM Engineering College, Kattankulathur, Tamil Nadu, India

    Subhransu Sekhar Dash

  3. Electrical Engineering, IIT Delhi, New Delhi, Delhi, India

    Bijaya Ketan Panigrahi

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Cite this paper

Vigneshwari, S., Aramudhan, M. (2015). Web Information Extraction on Multiple Ontologies Based on Concept Relationships upon Training the User Profiles. In: Suresh, L., Dash, S., Panigrahi, B. (eds) Artificial Intelligence and Evolutionary Algorithms in Engineering Systems. Advances in Intelligent Systems and Computing, vol 325. Springer, New Delhi. https://doi.org/10.1007/978-81-322-2135-7_1

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  • DOI: https://doi.org/10.1007/978-81-322-2135-7_1

  • Published:

  • Publisher Name: Springer, New Delhi

  • Print ISBN: 978-81-322-2134-0

  • Online ISBN: 978-81-322-2135-7

  • eBook Packages: EngineeringEngineering (R0)

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