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An Enhanced Model for Digital Reference Services

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Recent Advances on Soft Computing and Data Mining (SCDM 2020)

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Abstract

Digital Reference Service (DRS) play a vital role in the Digital Library (DL) research. DRS is a very valuable service provided by DL. Unfortunately, the reference service movement towards digital environment begins late, and this shift was not model based. So, a journey towards a digital environment without following a proper model raises some issues. A few researchers presented a general process model (GPM) in the late 1990s, but this process model could not overcome the problems of DRS. This paper proposes an enhanced model for DRS that use the storage and re-use mechanism with other vital components like DRS search engine and ready reference for solving the issues in DRS. Initially, storage and re-use mechanism are designed and finally, DRS search engine is designed to search appropriate answers in the knowledge base. We improved the GPM by incorporating the new components. The simulation results clearly states that the proposed model increased the service efficiency by reducing the response time from days to seconds for repeated questions and decreased the workload of librarians.

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Acknowledgments

The authors would like to thank Universiti Tun Hussein Onn Malaysia (UTHM) and Ministry of Higher Education (MOHE) Malaysia for financially supporting this Research under IGSP grants note U420 and under Trans-displinary Research Grant Scheme (TRGS) vote no. T003.

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Correspondence to Asim Shahzad or Nazri Mohd Nawi .

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Shahzad, A., Nawi, N.M., Mahdin, H., Khan, S.N., Hamid, N.A. (2020). An Enhanced Model for Digital Reference Services. In: Ghazali, R., Nawi, N., Deris, M., Abawajy, J. (eds) Recent Advances on Soft Computing and Data Mining. SCDM 2020. Advances in Intelligent Systems and Computing, vol 978. Springer, Cham. https://doi.org/10.1007/978-3-030-36056-6_1

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