Identifying effective criteria for author matching in bioinformatics

With the increasing development of information and scientific databases, collaboration has expanded in health sciences. This study aims to prioritize criteria that affect finding potential author matches bioinformatics using fuzzy Multiple Criteria Decision Making (MCDM) methods such as Analytical Hierarchy Process (AHP), Fuzzy Delphi Method (FDM), Triangular Numbers (TFN). To answer research questions, a mix documentary analysis is utilized. The stage involves collecting relevant documents resources purposive sampling approach ranking effective criteria. subsequent step experts determining priorities pairwise comparisons questionnaire. final weights are obtained based on purpose. shows 79 related purpose can be grouped into three general categories: behavioral, topological, content-based most recommending match “journal titles”, “citations”, “paper “affiliations”, “keywords”, “abstracts”. Among these criteria, citation paper titles have higher priority compared others. results indicate significant impact static scholar networks with text information. Furthermore, among number publications common specialized journals citations sought-after for highest similarity.