Machine learning approach for categorical document mining

The word text mining or document mining means automatic classification of text documents to different categories depending on their content. At present days this area of research is attracting many researchers due to increasing use of electronic documents in everyday life. In this paper authors have proposed a document mining method using Bisecting K-means algorithm, KNN classifier and Decision tree. There are many machine learning classification algorithms used for information retrieval. But most of them have very high computational complexity. So a method Bisecting K – Means clustering algorithm instead of normal K-means algorithm is used here and this approach trivially reduces the number of comparisons compared to others. The researchers also used decision tree at last to obtain the sub categories more accurately. After analysis it is found that the combination of Bisecting K Means and KNN classifier enhance the accuracy of the categorization. Accuracy of this proposed system is shown for each category at Result and discussion section.