文献类型：会议论文

英文题名：Research of Mining Algorithms for Uncertain Spatio-temporal Co-occurrence Pattern

作者：Wang, Zhanquan[1];Lu, Bowen[1];Ying, Fangli[1];Kong, Man[1];Tang, Minwei[1]

机构：[1]East China Univ Sci & Technol, Acad Informat Sci & Engn, Shanghai 200237, Peoples R China

会议论文集：9th International Conference on Knowledge and Smart Technology (KST)

会议日期：FEB 01-04, 2017

会议地点：Pattaya, THAILAND

语种：英文

外文关键词：component; Spatial Co-location; Spatiotemporal Co-occurrence; Uncertain data

摘要：Spatial Co-location pattern mining and Spatio-temporal Co-occurrence pattern mining are important directions of spatial data mining However, the existing relevant mining algorithms are computational expensive and the algorithms can't effectively deal with uncertain data which are wide spread in many areas. The fast co-occurrence data mining algorithms for the uncertain data are proposed by using the filter-refine method and efficient pruning strategy. The correctness, completeness and complexity of the proposed algorithms are analyzed, and the experimental data shows that the algorithms are effective and reasonable.