Identifying top researchers in specific fields or methods can be challenging with existing academic search tools. We propose a system that enables users to search for popular authors based on specific keywords or methods and explore their academic networks. The system retrieves recent influential papers, ranks authors using a weighted scoring mechanism that considers author positions and co-authorship patterns, and presents the results through an interactive web interface. Users can view authors in a sortable list or an interactive graph that visualizes collaborations. Experiments show that the system effectively identifies leading experts and their networks, helping students and researchers discover key contributors in targeted research areas.

错误:搜索内容不能为空,请输入英文关键词
错误:关键词超出字数限制,请精简
高级检索

AuthNet: A Framework for Research Expert Discovery and Network Visualization Based on Topic-Specific Queries

  • Dieu-Hien Nguyen,
  • Nguyen-Khang Le,
  • Minh Le Nguyen

摘要

Identifying top researchers in specific fields or methods can be challenging with existing academic search tools. We propose a system that enables users to search for popular authors based on specific keywords or methods and explore their academic networks. The system retrieves recent influential papers, ranks authors using a weighted scoring mechanism that considers author positions and co-authorship patterns, and presents the results through an interactive web interface. Users can view authors in a sortable list or an interactive graph that visualizes collaborations. Experiments show that the system effectively identifies leading experts and their networks, helping students and researchers discover key contributors in targeted research areas.