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Measuring the Effectiveness of Knowledge Driven Web Applications

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Advanced Topics in Intelligent Information and Database Systems (ACIIDS 2017)

Part of the book series: Studies in Computational Intelligence ((SCI,volume 710))

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Abstract

Today, web applications are often considered as real-life reflections of enterprises. Patrons do invest large finances. Besides, lot of time and effort are put in towards development and maintenance of the web applications. The effectiveness of such web applications is an indicator for both further investment and refinement of existing content, services and human resources. In this work, a new approach is proposed to quantify the effectiveness of knowledge driven web application. This is named as Unique Track Measure Orientation (UTMO). The proposed UTMO computes the effectiveness from navigation of different types of information in accordance with the business value. The business value could be anything-the brand value, turnover, or cumulative profit.

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Author information

Authors and Affiliations

  1. Greater Kolkata College of Engineering and Management, Dudhnai, India

    Supriya Chakraborty

  2. University of Calcutta, Kolkata, India

    Novarun Deb & Nabendu Chaki

Authors
  1. Supriya Chakraborty
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  2. Novarun Deb
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  3. Nabendu Chaki
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Corresponding author

Correspondence to Nabendu Chaki .

Editor information

Editors and Affiliations

  1. Faculty of Computer Sci. and Management, Wroclaw Univ. of Science and Technology Faculty of Computer Sci. and Management, Wroclaw, Poland

    Dariusz Król

  2. Faculty of Computer Sci. and Management, Wroclaw Univ of Science and Technology Faculty of Computer Sci. and Management, Wroclaw, Poland

    Ngoc Thanh Nguyen

  3. School of Advanced Sci. and Technology, Japan Advanced Inst. of Sci. and Tech School of Advanced Sci. and Technology, Ishikawa, Japan

    Kiyoaki Shirai

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Chakraborty, S., Deb, N., Chaki, N. (2017). Measuring the Effectiveness of Knowledge Driven Web Applications. In: Król, D., Nguyen, N., Shirai, K. (eds) Advanced Topics in Intelligent Information and Database Systems. ACIIDS 2017. Studies in Computational Intelligence, vol 710. Springer, Cham. https://doi.org/10.1007/978-3-319-56660-3_39

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  • DOI: https://doi.org/10.1007/978-3-319-56660-3_39

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  • Publisher Name: Springer, Cham

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  • Online ISBN: 978-3-319-56660-3

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