Suspicious Activity Detection System Steamer Algorithm Research

1. SAD: SUSPICIOUS
ACTIVITY DETECTION
SYSTEM
Project Supervisor: Sir Saad Razzaq
Data Mining

2. Team
Abdur Rahman

3. Agenda
Introduction
Problem
Statement
Scope of
Project
Objective
Introduction
Reasons
Complications
Resolution
Elaborating
Working
Results
Techniques
Outcomes
Queries
Conclusion

4. Problem Statement
• Internet has now become a social media platform where people get every type of
information and share their views about it.
• Due to increase in popularity of web forms and blogs , sifting through all the data posted
their manually is impossible.
• The size of post and number of comments is increasing day by day and hence most of
the material found is not reliable.
• Sometime these views initiate a chain reaction of comments giving rise to illegal and
suspicions activities.
• propagation of copyrighted movies, aggressive messages, gambling and propaganda
against government.
• So their should be a system to check these view and comments to highlight those
platforms where illegal actions are performed or not.

5. Scope of Project
• Data Crawling from blogs
• Stemming algorithm to get root words
• Suspicious Activity detection technique

6. Objective
Accuracy
?

7. Significance
• Process is straightforward
• Natural Language processing is used
• Custom-based dictionary to cover every keyword
• Easy to use

8. Reasons
• Increased illegal activity on blogs and forums
• No regulatory mechanism
• Data is thought to be unimportant
• Increased user interest in blogs
• Manual checking of blogs is impossible

9. Complications
• Crawling data is not allowed
• Natural language Processing
• Getting root words from comments
Suspicious

10. Resolution
• Identify comments class to crawl data

11. Resolution
• Getting root words to improve activity detection and less data
redundancy

12. Resolution
• Converting stemmed sentence into single words
• Identifying suspicious words using library and then displaying result to
user

13. Working

14. Working

15. Working

16. CONCLUSION

17. Result
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Chart Title
Time no. of comments comment length
Crawler Efficiency

18. Result
Stemmer Efficiency
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1 2 3 4 5
STEMMER EFFICIENCY
Words sent to stemmer Accurately Stemmed

19. Result
0
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1 2 3 4 5
Achieved Detection Expected Detection
SAD System efficiency

20. THANK YOU