时间:2016年12月28日下午1:30-3:30

地点:中央财经大学沙河校区,学院楼4号楼,318会议室

内容:

Knowledge Organization Systems (KOS) (e.g., classification schemes, taxonomies and ontologies) have long been established as a tool to represent organized interpretation of knowledge structures. Various types of KOS such as NSFC discipline tree for research projects, subject categories for research publications, classifications schemes for research patents are constructed for research management purpose. However, the incompatible KOS, together with information proliferation in the Big Data Era, impose great challenges for effective research management from heterogeneous information. My research aims to facilitate interoperability among heterogeneous research information sources by leveraging metadata analysis and social network analysis. In the published paper in Scientometrics, a novel multi-faceted method was designed to measure the similarity between two classes based on three important facets, namely descriptors, individuals, and semantic neighborhood. The method was evaluated based on two main KOS that need mapping for information management and policy-making in NSFC, and shown satisfying results. The interoperability among heterogeneous KOS was resolved to enhance the access to heterogeneous scientific resources andthe development of appropriate research analytics policies.

报告人简介:

  杜玮博士,现为香港城市大学商学院博士后研究员，在Scientometrics期刊、Journal of Network and Computer Applications期刊、ICIS和HICSS等国际期刊和会议上发表论文多篇;香港城市大学商学院信息系统专业博士，获全额奖学金，主要研究兴趣为社会网络分析、社交平台、推荐系统、数据挖掘等.