MINING CO-LOCATION PATTERNS WITH CLUSTERING ITEMS FROM SPATIAL DATA SETS

Mining Co-Location Patterns with Rare Events from Spatial Data Sets

A co-location pattern is a group of spatial features/events that are frequently co-located in the same region. For example, human cases of West Nile Virus often occur in regions with poor mosquito control and the presence of birds. For colocation pattern mining, previous studies often emphasize the equal participation of every spatial feature. As a result, interesting patterns involving events ...

Mining Co-location Patterns from Spatial Data Using Rulebased Approach

Co-location pattern is a group of spatial features/events that are frequently co-located in the same region. The co-location pattern discovery process finds the subsets of features frequently located together. Co-location rules are identified by spatial statistics or data mining techniques. A co-location algorithm has been used to discover the co-location patterns which possess an ant monotone ...

Clustering Assisted Co-location Pattern Mining for Spatial Data

The importance of spatial data mining is growing with the increasing incidence and importance of large spatial datasets repositories of remote-sensing images, location based mobile app data, satellite imagery, medical data and crime data with location information, three dimensional maps, traffic data and many more. However, as classical data mining techniques are often inadequate for spatial da...

A Framework for Discovering Co-Location Patterns in Data Sets with Extended Spatial Objects

Mining Of Spatial Co-location Pattern from Spatial Datasets

Spatial data mining, or knowledge discovery in spatial database, refers to the extraction of implicit knowledge, spatial relations, or other patterns not explicitly stored in spatial databases. Spatial data mining is the process of discovering interesting characteristics and patterns that may implicitly exist in spatial database. A huge amount of spatial data and newly emerging concept of Spati...