A Hierarchical Multi-Relational Clustering Algorithm Based on Modal Logic
For datasets contained multi interrelated tables, multi-relational clustering divides target objects into clusters according to their attributes and features of objects related to them directly or indirectly. Due to the actual business, all target objects dont exist information in every nontarget relation, so target objects may be described by information of different order. To get information about one-to-many relationships, it is often unable to reflect original distribution of data if using statistics directly. To solve these problems, we propose a new method to model multi-relational data set based on modal logic, define distance between objects, and clustering by means of original features of all objects. Experiments indicate that our method can dispose information of different order effectively, and obtain more accurate and reasonable clustering results.
Yuan Cheng Shaobin Huang Tianyang Lv Guofeng Liu
College of Computer Science and Technology Harbin Engineering University Harbin Engineering University
国际会议
2011 4th International Congress on Image and Signal Processing(第四届图像与信号处理国际学术会议 CISP 2011)
上海
英文
2486-2490
2011-10-15（万方平台首次上网日期，不代表论文的发表时间）