Abstract
As fake website developers become more innovative, so too must the tools used to protect Internet users. A proposed system combines a support vector machine classifier and a rich feature set derived from website text, linkage, and images to better detect fraudulent sites.
Original language | English (US) |
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Pages | 78-86 |
Number of pages | 9 |
Volume | 42 |
No | 10 |
Specialist publication | Computer |
DOIs | |
State | Published - 2009 |
Keywords
- Artificial Intelligence
- Computer systems organization
- Computing methodologies
- Machine learning
- Natural language processing
- Web text analysis
ASJC Scopus subject areas
- General Computer Science