Findme-scholar: a contextual researcher recommender system for enhancing research collaboration using adaptive topic interest area modelling

Abstract

Identifying potential research collaborators with aligned expertise and complementary interests remains a persistent challenge, particularly in multidisciplinary and large-scale academic environments. This paper introduces Findme-Scholar, a contextual researcher recommender system aimed at enhancing research collaboration through adaptive topic interest area modelling. The system dynamically captures researchers' evolving thematic interests by analyzing publication metadata and semantic content to provide context-aware recommendations that surpass traditional static profile matching approaches. Our method successfully recommended researchers without prior co-authorship links to the target individual, demonstrating its ability to identify potential collaborators beyond existing networks. This result reflects the method’s effectiveness in capturing thematic and contextual similarities to discover relevant yet previously unconnected researchers.

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  Findme-Scholar models evolving research interests for better collaboration.
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  Recommends collaborators beyond existing co-authorship networks.
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  Uses semantic and metadata analysis for context-aware suggestions.