摘要
在科技项目评审环节中,往往每组同时有多个项目和多位评审专家,其中每个项目都有其所覆盖的专业领域,而每位专家又有其所研究的专业领域,如何科学且自动地根据待评审科技项目所涵盖的专业领域,从候选专家库中找出合适的评审专家组合团体具有很实际的研究意义.对此本文提出了一种基于贪心算法的科技项目评审专家多重匹配模型,该模型应用于已经建立起关联的“项目-领域”与“专家-领域”两个相关性矩阵上,通过分别计算科技项目及评审专家团体所对应于专业领域上的离散分布,并利用合适的评价函数综合衡量待审科技项目与评审专家组合之间的匹配度,最终求出最优的评审专家组合来作为该期科技项目的最终评审专家团体.本文通过使用电力行业数据集进行多次实验,结果表明该模型能有效地进行科技项目评审专家的匹配,并具有较高的合理性与准确性,在解放人力成本提高评审工作效率的同时,也杜绝了传统人工遴选专家过程中所出现纰漏以及评审不公现象的发生.
Multiple technology projects in a group are evaluated by several experts.Each project covers certain fields and each expert has his/her own advantageous fields.Thus,it is a significant challenge to scientifically and automatically group experts in suitable fields of relevant projects from a large number of candidates.This study proposes a multi-match model GIS of evaluation experts for technology projects based on the greedy algorithm.This model is applied to the two associated“project-field”and“expert-field”correlation matrices.Specifically,it separately calculates the discrete distribution of projects and experts in each field.Then it uses a proper evaluation function to measure the project-expert match and finally obtains the optimal team.The experiments based on the data sets in the power industry show that this model can match the experts with the technology projects and thus has high rationality and accuracy.It avoids the careless mistakes and unfairness in traditional expert selection while reducing human costs.
作者
曹滔宇
熊永平
史梦洁
徐会芳
谷纪亭
CAO Tao-Yu;XIONG Yong-Ping;SHI Meng-Jie;XU Hui-Fang;GU Ji-Ting(State Key Laboratory of Networking and Switching Technology,Beijing University of Posts and Telecommunications,Beijing 100876,China;Artificial Intellegence Applications Institute,China Electric Power Research Institute Co.Ltd.,Beijing 102209,China;State Grid Zhejiang Economic Research Institute Co.Ltd.,Hangzhou 310001,China)
出处
《计算机系统应用》
2021年第4期168-174,共7页
Computer Systems & Applications
基金
国家电网公司总部科技项目(SGTYHT/18-JS-206)。
关键词
专家遴选
多重匹配模型
贪心算法
离散分布
expert selection
multi-matching model
greedy algorithm
discrete distribution
