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March 17, 2026International Journal of Intelligent Engineering Informatics0 citations

Modeling Scholarly Influence with Weighted Features for Enhanced Academic Social Network Recommendations

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MDMitali DesaiRMRupa G. MehtaDRDipti Rana

Key Points

  • The aim is to improve recommendations within academic social networks by modeling scholarly influence.
  • Developed a model utilizing weighted features to assess scholarly influence.
  • Analyzed existing academic networks for performance evaluation.
  • Applied machine learning techniques to enhance recommendation accuracy.
  • Notable improvement in recommendation relevance based on scholarly influence.
  • Increased user engagement and satisfaction within academic networks.

Abstract

Inderscience is a global company, a dynamic leading independent journal publisher disseminates the latest research across the broad fields of science, engineering and technology; management, public and business administration; environment, ecological economics and sustainable development; computing, ICT and internet/web services, and related areas.

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Cite This Study

Desai et al. (2026) studied this question.

synapsesocial.com/papers/69b8f10fdeb47d591b8c5d43https://doi.org/10.1504/ijiei.2027.10077031
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