Implementing a data mining solution for enhancing carpet manufacturing productivity
Knowledge-Based Systems
Unsupervised image retrieval framework based on rule base system
Expert Systems with Applications: An International Journal
A support vector machine-based model for detecting top management fraud
Knowledge-Based Systems
Supporting image retrieval framework with rule base system
Knowledge-Based Systems
ACIIDS'12 Proceedings of the 4th Asian conference on Intelligent Information and Database Systems - Volume Part II
Hi-index | 0.00 |
This paper proposed a decision tree based classification method to detect e-mails that contain terrorism information. The proposed classification method is an incremental and user-feedback based extension of a decision tree induction algorithm named Ad Infinitum. We show that Ad Infinitum algorithm is a good choice for threatening e-mail detection as it runs fast on large and high dimensional databases, is easy to tune and is highly accurate, outperforming popular algorithms such as Decision Trees, Support Vector Machines and Naive Bayes. In particular, we are interested in detecting fraudulent and possibly criminal activities from such e-mails.