流程监控与评估中多元数据整合研究

项目名称： 流程监控与评估中多元数据整合研究

项目编号： No.71461023

项目类型： 地区科学基金项目

立项/批准年度： 2015

项目学科： 管理科学

项目作者： 王珊珊

作者单位： 内蒙古大学

项目金额： 34万元

中文摘要： 本项目立足于企业缺乏大数据价值有效挖掘的现状,多元数据整合为大数据有效挖掘前提的事实,针对多元数据复杂性即互相隔绝,类型异构,关联度较低造成了数据整合难的问题以及目前学术界较为缺乏多元数据整合研究内容的现实,提出了以流程监控与评估为研究背景,首先利用领域知识与相关理论分析数据整合时对多元化数据内容的选择,以及数据整合位置点的选择,然后开发设计数据整合所需的语义知识模型,知识库,数据模型,数据分析算法等技术,并应用仿真与实际数据案例对整合方法进行评估.项目为大数据有效挖掘奠定了理论基础,同时还开发了相关支持技术,为流程监控与评估和其他商业领域提供了有效利用大数据的理论与技术方案.

中文关键词： 多元数据整合；大数据；流程监控与评估；语义本体；数据挖掘

英文摘要： Big data is changing our's life and business environment, especially it brings organizations great business value,however, most of organizations has difficulty in mining knowledge and using big data.Manager and Knowledge workers usually lose themselves in the big, complex,low correlated and multi-sources data, thus it is important for them to aggregate multi-sources data before mining knowledge from big data. Research for big data attracts great volume of attention from both scholars and business organizations, however, few research has focus on multi-sources data aggregation. Therefore, in this project,in the context of business process monitoring and evaluation,how to choose data among multi-sources data for a particuliar business problem and position for organizing those chosen data is studied from domain knowledge and theory perspective, and then on the basis of which, techiniques for these chosen data aggregation is developed including Semantic ontology, knowledge bases, and algorithms for data analysis. Finally, simulation and case study are conducted for evaluating the whole methodology proposed in the project for multi-sources data aggregation. The expected contributions are as follows: firstly, with the domain knowledge and theory,the difficulty in multi-sources data aggregation caused by complex characteristic including low-correlated,heterogenous is alleviated by developing Semantic ontology,knowledge bases, related data analysis algorithms;secondly, business process monitoring and evaluation is supported by aggregating business process logs,context and Internet user generated content,based on which, business process monitoring and evaluation can enahnce organization's capability in serving customers and make organizations more adaptable to dynamic enviroment;Thirdly, the methodology provided in this project benefits big data utilization and promotes knowledge quality mined from big data.

英文关键词： multi-sources data aggregation;big data;business process monitoring and evaluation;semantic ontology;data mining