Text Document Classification and Pattern Recognition
Qin Wu, Eddie Fuller, Cun‐Quan Zhang · 2009
In this extended abstract, a novel approach is proposed for text pattern recognition. Instead of the traditional models which are mainly based on the frequency of keywords for text document classification, we introduce a new graph theory model which is constructed based on both information about frequency and position of keywords. We applied this new idea to the detection of fraudulent emails written by the same person, and plagiarized publications. The results on these case studies show that this new method performs much better than traditional methods.