A Combined Co-location Pattern Mining Approach for Post-Analyzing Co-location Patterns
Yuan Fang, Lizhen Wang, Junli Lu, Lihua Zhou
Available Online January 2016.
- https://doi.org/10.2991/icaita-16.2016.10How to use a DOI?
- co-location pattern mining; combined mining; post-analysis
- The co-location pattern mining discovers the subsets of spatial features which are located together frequently in geography. However, the huge number of the co-location mining results limit the usability of co-location patterns. Furthermore, users hardly identify and understand the interesting knowledge directly from the single co-location pattern.In this paper, we studied the problem of extractingcombined co-location patterns from a large collectionof prevalent co-location patterns.We first gave the definitions of atomic co-location pattern, combined co-location pattern pair and cluster; secondly, we designed a series of interesting metrics to measure the interestingness of atomic co-location patterns, combined co-location pattern pairs and clusters; thirdly, an combined co-location mining algorithm and redundant elimination strategies were proposed. The experiments evaluated the method both on real data sets and syntheticdata sets. The results show that our method can effectively discover combined co-location patterns.
- Open Access
- This is an open access article distributed under the CC BY-NC license.
Cite this article
TY - CONF AU - Yuan Fang AU - Lizhen Wang AU - Junli Lu AU - Lihua Zhou PY - 2016/01 DA - 2016/01 TI - A Combined Co-location Pattern Mining Approach for Post-Analyzing Co-location Patterns BT - Proceedings of the 2016 International Conference on Artificial Intelligence: Technologies and Applications PB - Atlantis Press SP - 38 EP - 43 SN - 1951-6851 UR - https://doi.org/10.2991/icaita-16.2016.10 DO - https://doi.org/10.2991/icaita-16.2016.10 ID - Fang2016/01 ER -