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WISHFUL - Website Extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage

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Information Integration and Web Intelligence (iiWAS 2023)

Part of the book series: Lecture Notes in Computer Science ((LNCS,volume 14416))

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Abstract

Extracting information from diverse websites is increasingly important, especially for analyzing vast data sets to detect trends, gain insights. By studying job ads, researchers can monitor employer demand shifts, assisting policymakers in aiding affected workers and industries. However, extraction faces challenges like varied website formats, dynamic content, and duplicate data. This study introduces a method for extracting data from diverse private university websites involving keyword identification, website categorization, and extraction pipelines.

This work has been partially funded by the BMBF (FKZ: 16KOA008).

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Author information

Authors and Affiliations

  1. German Centre for Higher Education Research and Science Studies, Hannover, Germany

    Saijal Shahania & David Broneske

  2. Faculty of Computer Science, University of Magdeburg, Magdeburg, Germany

    Saijal Shahania, Myra Spiliopoulou & David Broneske

Authors
  1. Saijal Shahania
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  2. Myra Spiliopoulou
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  3. David Broneske
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Corresponding author

Correspondence to Saijal Shahania .

Editor information

Editors and Affiliations

  1. Monash University, Melbourne, VIC, Australia

    Pari Delir Haghighi

  2. La Trobe University, Melbourne, VIC, Australia

    Eric Pardede

  3. University of Auckland, Auckland, New Zealand

    Gillian Dobbie

  4. University of Auckland, Auckland, New Zealand

    Vithya Yogarajan

  5. Udayana University, Denpasar, Indonesia

    Ngurah Agus Sanjaya ER

  6. Johannes Kepler University Linz, Linz, Austria

    Gabriele Kotsis

  7. Johannes Kepler University Linz, Linz, Austria

    Ismail Khalil

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© 2023 The Author(s), under exclusive license to Springer Nature Switzerland AG

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Cite this paper

Shahania, S., Spiliopoulou, M., Broneske, D. (2023). WISHFUL - Website Extraction of Institutional Sources with Heterogeneous Factors and User-Driven Linkage. In: Delir Haghighi, P., et al. Information Integration and Web Intelligence. iiWAS 2023. Lecture Notes in Computer Science, vol 14416. Springer, Cham. https://doi.org/10.1007/978-3-031-48316-5_3

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  • DOI: https://doi.org/10.1007/978-3-031-48316-5_3

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-031-48315-8

  • Online ISBN: 978-3-031-48316-5

  • eBook Packages: Computer ScienceComputer Science (R0)

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