Abstract:
In this paper we describe the new classification algorithm for web page classification is ant colony optimization
algorithm. The algorithm’s aim is to solve for discrete problem and discreteness of text documents’ features. In this paper, the
system consists two parts for classification: training processing and classifying processing. In training process, the system
removes the unnecessary part of the web page in preprocessing step. After preprocessing step, each text is represented by vector
space model using TF-IDF formula. In the classifying process, the testing web page is tested to classify appropriated class label
by ant colony algorithm and ant colony algorithm works to find the optimal path or optimal class for text features by matching
during iteration in the algorithm. The satisfactory accuracy of classification can be getting in this system.
