大数据 ›› 2020, Vol. 6 ›› Issue (6): 0-.doi: 10.11959/j.issn.2096-0271.2020059

• 应用 •    

基于关系图谱的人岗关系研究

王晓萍1,郭梦洁2,3,岳婧雯2,3   

  1. 1 上海市经济和信息化委员会信息中心,上海 200125
    2 复旦大学计算机科学技术学院,上海 201203
    3 上海市数据科学重点实验室,上海 201203
  • 出版日期:2020-11-15 发布日期:2020-12-12
  • 作者简介:王晓萍(1977- ),上海市经济和信息化委员会信息中心高级工程师,主要研究方向为大数据、政府信息化|郭梦洁(1994- ),复旦大学计算机科学技术学院、上海市数据科学重点实验室硕士生,主要研究方向为大数据、网络表示学习方法|岳婧雯(1997- ),复旦大学计算机科学技术学院、上海市数据科学重点实验室硕士生,主要研究方向为大数据、网络表示学习方法
  • 基金资助:
    国家自然科学基金资助项目(1636207);国家自然科学基金资助项目(6167115);上海市经济和信息化委员会市级部门预算资金项目(201859971904)

Research on person-position relationship based on relation graph

Xiaoping WANG1,Mengjie GUO2,3,Jingwen YUE2,3   

  1. 1 Shanghai Municipal Commission of Economy and Informatization,Information Center,Shanghai 200125,China
    2 School of Computer Science,Fudan University,Shanghai 201203,China
    3 Shanghai Key Laboratory of Data Science,Shanghai 201203,China
  • Online:2020-11-15 Published:2020-12-12
  • Supported by:
    The National Natural Science Foundation of China(1636207);The National Natural Science Foundation of China(6167115);The Foundation of Shanghai Municipal Commission of Economy and Informatization(201859971904)

摘要:

利用现有的数据进一步挖掘分析并帮助干部组织工作,是一个既有挑战又具有潜力的方向。针对干部信息数据的特点,使用基于关系图谱的人岗相宜研判方法分析领导班子,通过整合干部履历表以及人员基本信息库中的多源信息,构建关系图谱;将基于网络表示学习算法提取的关系图谱中的节点及关系等信息作为特征并输入分类模型,实现人岗关系研判。实验结果表明,基于关系图谱的方法可以很好地捕获人员和岗位之间的复杂关系信息,准确地判断人岗关系。

关键词: 人岗关系分析, 关系图谱, 网络表示学习, 大数据

Abstract:

Utilizing the existing data to further analyze and help leaders organize their work is a potential and challenging direction.According to the characteristics of leader information data,the leadership team was analyzed using the person-position relationship judgment method based on relation graph,a relation graph was built by integrating the leader resume and the multi-source information from the database.Then the information such as nodes and relationships in the relation graph extracted by the network representation learning method was used as features to input into the classification model.By using the proposed model,the relationship between people and positions can be inferred.The experimental results show that the method based on relation graph can well capture the complex relationship between people and positions,and can accurately judge the person-position relationship.

Key words: analysis on person-position relationship, relation graph, network representation learning, big data

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