报告题目：Research on Algorithms and Data Modeling for Big Data Analytics on Social Learning and Knowledge Retrieval Systems with the Approaches of Clustering Attributed Graphs
报 告 人：Xiaokun Zhang （张晓坤）教授
主 持 人：王克勤副教授
Traditionally, in management information systems (or collaborative learning systems in particular), user (or learner) group’s detection algorithms primarily focus on the network structure, while clustering algorithms mostly consider only individual user’s attributes. Recent researches reveal that an algorithm upon separated two sources of information may fail to account for important structure in the data. However, combing individual user’s attributes and network topology for user group’s analytics is challenging, partially due to the needs to integrate two very different modalities of information. This direction has drawn intensive researches recently towards social network analytics, but researchers seem to do little work to address the issues and innovate methods and theory to leverage social learning analytics in collaborative work environment or learning systems.
The goal of this talk is to introduce the concepts of users’ (or learners’) interrelated data models, algorithm analyses and implementations for social learning analytics with the integrated clustering attributed graphs. Ultimately, given the application domain in smart and collaborative learning systems, our own learning environment, and the learning environment and cases in other universities will be considered while the dataset and algorithm models are analyzed via the proposed approaches. The approaches can be extended to the application domains where intensive user’s interactions and collaborative knowledge sharing are concerned to leverage better collaboration and workflow management.
张晓坤博士是加拿大Athabasca 大学终身教授。自2001 年起任职于该校的计算与信息系统学院。毕业于西北工业大学飞行器制造工程系，曾任西北工业大学机电工程学院 教授，在美国Iowa 大学智能系统实验室做访问教授，在加拿大Calgary 大学智能制造工程专业做博士后研究。他是IEEE Systems, Man, and Cybernetics 学会Computer Supported Cooperative Work in Design 技术委员会委员。研究领域涉及复杂协调计算的工程应用与软件技术研究。目前的研究生指导及研究兴趣侧重于大数据建模分析的应用方法研究及其工业应用计算软件系统的应用研究。