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Efficient Management of Web Data by Applying Web Mining Pre-processing Methodologies

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Book cover Software Engineering

Part of the book series: Advances in Intelligent Systems and Computing ((AISC,volume 731))

Abstract

Web usage mining is defined as the application of data mining techniques to extract interesting usage patterns from Web data. Web data provides the information about Web user’s behavior. Pre-processing of Web data is an essential process in Web usage mining. This is used to convert the raw data into processed data which is necessary for Web mining task. In this research paper, author proposed the effective Pre-processing methodology which involves field extraction, significant attributes selection, data selection, and data cleaning. The efficient proposed methodology improves the quality of Web data by managing missing values, noise, inconsistency, and incompleteness which is usually found attached with data. Moreover, obtained results of pre-processing will be further used in frequent pattern discovery.

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Author information

Authors and Affiliations

  1. Department of Computer Science & Applications, Kurukshetra University, Kurukshetra, Haryana, India

    Jaswinder Kaur & Kanwal Garg

Authors
  1. Jaswinder Kaur
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  2. Kanwal Garg
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Corresponding author

Correspondence to Jaswinder Kaur .

Editor information

Editors and Affiliations

  1. Bharati Vidyapeeth’s Institute of Computer Applications and Management (BVICAM), New Delhi, Delhi, India

    M. N. Hoda

  2. Department of Computer Engineering, YMCAUST, Faridabad, Haryana, India

    Naresh Chauhan

  3. Department of Computer Science, University of Kashmir, Srinagar, Jammu and Kashmir, India

    S. M. K. Quadri

  4. Department of Information Technology and Systems, Indian Institute of Management Rohtak, Rohtak, Haryana, India

    Praveen Ranjan Srivastava

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Kaur, J., Garg, K. (2019). Efficient Management of Web Data by Applying Web Mining Pre-processing Methodologies. In: Hoda, M., Chauhan, N., Quadri, S., Srivastava, P. (eds) Software Engineering. Advances in Intelligent Systems and Computing, vol 731. Springer, Singapore. https://doi.org/10.1007/978-981-10-8848-3_11

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  • DOI: https://doi.org/10.1007/978-981-10-8848-3_11

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  • Publisher Name: Springer, Singapore

  • Print ISBN: 978-981-10-8847-6

  • Online ISBN: 978-981-10-8848-3

  • eBook Packages: EngineeringEngineering (R0)

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