Advanced Academic Team Worker Recommendation Models
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Abstract (arXiv)
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.
Key facts. No citing papers in the map yet (data through 7 Oct 2026). Builds on 4 of its 25 references that are in the map. First posted on arXiv 7 Feb 2024.
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References · 4
- 2014DeepWalk: Online Learning of Social Representationscited by 1,543
- 2019Position-aware Graph Neural Networkscited by 203
- 2020KompaRe: A Knowledge Graph Comparative Reasoning Systemcited by 20
- 2023Conversational Question Answering with Reformulations over Knowledge Graphcited by 4
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