English

Advanced Academic Team Worker Recommendation Models

Information Retrieval 2024-02-28 v1 Artificial Intelligence

Abstract

Collaborator recommendation is an important task in academic domain. Most of the existing approaches have the assumption that the recommendation system only need to recommend a specific researcher for the task. However, academic successes can be owed to productive collaboration of a whole academic team. In this work, we propose a new task: academic team worker recommendation: with a given status: student, assistant professor or prime professor, research interests and specific task, we can recommend an academic team formed as (prime professor, assistant professor, student). For this task, we propose a model CQBG-R(Citation-Query Blended Graph-Ranking). The key ideas is to combine the context of the query and the papers with the graph topology to form a new graph(CQBG), which can target at the research interests and the specific research task for this time. The experiment results show the effectiveness of the proposed method.

Keywords

Cite

@article{arxiv.2402.16876,
  title  = {Advanced Academic Team Worker Recommendation Models},
  author = {Mi Wu},
  journal= {arXiv preprint arXiv:2402.16876},
  year   = {2024}
}
R2 v1 2026-06-28T15:00:49.668Z