Parallel Approach For Finding Co-Location Patterns - Sheshikala Martha
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The book discuss about the spatial co-location mining which finds the co-locations parallel which reduces the time complexity. Spatial co-location patterns represent a subset of features whose instances are frequently co-located in close proximity; For example Mountain area and new truck purchased are frequently co-located patterns, indicating that a person living close to mountainous areas is likely to buy ... Full description
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Description
The book discuss about the spatial co-location mining which finds the co-locations parallel which reduces the time complexity. Spatial co-location patterns represent a subset of features whose instances are frequently co-located in close proximity; For example Mountain area and new truck purchased are frequently co-located patterns, indicating that a person living close to mountainous areas is likely to buy a truck. Since the instances of spatial features are embedded in a continuous space and share a variety of spatial relationships the implementation of co-location mining can be taken as a challenge.
More Information
| Author | Sheshikala Martha |
|---|---|
| Publisher | Scholars' Press |
| Release year | 2018 |
| Cover type | Softcover |
| EAN | 9786202311038 |