The Compare Two Automated Text Categorization Algorithms Based On The Open Telephone Of Mayor

With the development of computer technolog,a large number of documents have become increase rapid.Because information expand apace,so how to use the information apace and effectively has become a new question fou us.We adopt manual classifier to deal with the information ago,but the efficiency is very low for the too much text information. Therefore,information processing turns and important for us to get useful information.So automated text categorization based on machine learning has becoming a important research domain.The advantages of this approach over the manual approach are a very good effectiveness ,considerable savings in terms of expert labor power,and straightforward portability to different domains.This survey introduces the definition of automated text categorization,the system of text categorization and the approaches to text categorization based on machine learning.We introduce in detail Naive Bayesclassifier and k-Nearest Neighbor method and implement two approaches.We solve the actual question and evaluate two classified approaches.We also compare the index of two classified approaches and discuss correlative questions.