# SASB: S patial A ctivity S ummarization using B uffers - PowerPoint PPT Presentation

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SASB: S patial A ctivity S ummarization using B uffers. Atanu Roy & Akash Agrawal. Overview. Motivation Problem Statement Computational Challenges Related Works Approach Examples Conclusion. Motivation. Applications in domains like Public safety Disaster relief operations.

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SASB: S patial A ctivity S ummarization using B uffers

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## SASB: Spatial Activity Summarization using Buffers

Atanu Roy & AkashAgrawal

### Overview

• Motivation

• Problem Statement

• Computational Challenges

• Related Works

• Approach

• Examples

• Conclusion

SASB

### Motivation

• Applications in domains like

• Public safety

• Disaster relief operations

### SASB Problem Statement

• Input

• A spatial network,

• Set of activities & their location in space,

• Number of buffers required (k),

• A set of buffer (β),

• Output

• A set of k active buffers, where

• Objective

• Maximize the number of activities covered in the kbuffers

• Constraints

• Minimize computation costs

### Definitions

• Constant Area Buffers

• Node buffers

• Path buffers

### Computational Challenges

• SASB is NP-Hard

• Proof:

• KMR is a special case of SASB

• Buffers have width = 0

• KMR is proved to be NP-Complete

• SASB is at least NP-Hard

### Contributions

• Definition SASB problem

• NP-Hardness proof

• Combination of geometry and network based summarization.

• First principle examples

### Greedy Approach

Choice of k-best buffers

• Repeat k times

• Choose the buffer with maximum activities

• Delete all activities contained in the chosen buffer from all the remaining buffers

• Replace the chosen buffer from buffer pool to the result-set

### Conclusion

• Provides a framework to fuse geometry and network based approaches.

• First principle examples indicates it can be comparable with related approaches.

### Acknowledgements

• CSci 8715 peer reviewers who gave valuable suggestions.