MPCPM: Multi-level Prevalent Co-location Pattern Miner

Prevalent co-location pattern (PCP) mining are crucial in fields like medicine, biology, and urban planning to identifies spatial relationships between objects or their simultaneous occurrences. However, challenges such as dealing with heterogeneous spatial data and high computational costs for mining multilevel PCPs persist. This demonstration presents MPCPM (Multi-level Prevalent Co-location Pattern Miner), a system for users who are not only interested in co-location patterns and their levels but also in the high performance of mining SCPs. Users give a spatial data set, the designed miner evaluate and identifies SCPs which are global and local. We evaluate and identify the prevalent co-location patterns which are global and local. Additionally, MPCPM also cites and represents the sets of instances that make up the PCP to provide more information and help the decision making.