当前位置: X-MOL 学术Knowl. Based Syst. › 论文详情
Cross Multi-Type Objects Clustering in Attributed Heterogeneous Information Network
Knowledge-Based Systems ( IF 5.101 ) Pub Date : 2020-01-07 , DOI: 10.1016/j.knosys.2019.105458
Sheng Zhou; Jiajun Bu; Zhen Zhang; Can Wang; Lingzhou Ma; Jianfeng Zhang

Real-world networks usually consist of a large number of interacting, multi-typed components which are usually referred as heterogeneous information networks (HIN). HIN that associated with various attributes on nodes is defined as attributed HIN (or AHIN). Clustering is a fundamental task for HIN and AHIN. However, most of the current existing methods focus on single type nodes and there is very limited existing work that groups objects of different types into the same cluster. This is largely due to the reasons that object similarities can either be attribute-based or link-based between same type of nodes and it is challenging to incorporate both in a unified framework. To bridge this gap, in this paper, we propose a framework, namely Cross Multi-Type Objects Clustering in Attributed Heterogeneous Information Network, or CMOC-AHIN, to integrate both the attribute information and multi-type node clustering in a principled way. We empirically show superior performances of CMOC-AHINon three large scale challenging data sets and also summarize insights on the performances compared to other state-of-the-arts methodologies.
更新日期:2020-01-07

 

全部期刊列表>>
Springer Nature 2019高下载量文章和章节
化学/材料学中国作者研究精选
《科学报告》最新环境科学研究
ACS材料视界
自然科研论文编辑服务
中南大学国家杰青杨华明
剑桥大学-
中国科学院大学化学科学学院
材料化学和生物传感方向博士后招聘
课题组网站
X-MOL
北京大学分子工程苏南研究院
华东师范大学分子机器及功能材料
中山大学化学工程与技术学院
试剂库存
天合科研
down
wechat
bug