文献类型：期刊文献

英文题名：Research on Algorithms of Positive and Negative Co-occurrence in Spatio-temporal Datasets

作者：Du, Jing[1]; Wang, Zhanquan[1]; Ye, Mengfei[1]

机构：[1] East China University of Science and Technology, School of Information Science and Engineering, Shanghai, China

年份：2022

外文期刊名：ICSAI 2022 - 8th International Conference on Systems and Informatics

收录：EI(收录号：20230513463481)

语种：英文

摘要：Discovering spatio-temporal co-occurrence patterns is a significant issue in many fields. Previous algorithms simply looked for positive patterns when mining spatial co-occurrence patterns. However, patterns with strong negative associations are ignored. This paper proposed a novel algorithm for mining both positive and negative co-occurrence patterns. We introduced the notions of positive and negative co-occurrence patterns, and positive and negative co-occurrence patterns are mined by using an effective pruning strategy. This paper analyzed the completeness and correctness of the algorithm. We conducted experiments using both real and synthetic data sets to validate the effectiveness and efficiency of the suggested method. ? 2022 IEEE.