The Design And Implementation Of The Spam Message Interception System On Android Platform

In recent years,along with the rapid development of mobile communication technology,smart phone has become one of the best essential communication tools in people's lives.As a convenience and affordable information carrier,mobile phone short message is closely linked with people's lives,providing an important way for the majority of mobile phone users to exchange information.However,with the popularity of short message,spam messages appear and bring a lot of trouble,seriously affecting people's normal life.These spam messages are not only useless to people,but also even harmful.Currently,the government has issued laws to manage the spam messages.But since spam messages are hidden,flexible,and have many other features,it is difficult to rely solely on legal means to effectively improve the situation.So spam messages interception technology has become the key to solving the problem,and intercepting on client is able achieve real-time filtering of spam messages.Therefore researching and designing a spam messages interceptor system of mobile phone on the client will be.an important means to solve this social problem,spam messages.Text classification technology is to determine the category of text through computer text parsing,with the relevant statistical data.Bayes classification is much commonly used as a text classification technology.It is referred to a class of classification algorithm which is based on the Bayes theorem.Naive Bayes classification algorithm is the most classical and is easy to be understood.The algorithm determines the category which has the maximum probability of appearance under the conditions of classify items appearing.Typically,the SMS text is seen as a combination of several feature words that can characterize the properties of text types.Using the Chinese word segmentation technology to determine the feature words of text and combining with Naive Bayes classification algorithm,can achieve an SMS text classification and identify the spam messages.This paper designs and implements a spam messages interceptor system based on intelligent text classification.This system operates on Android platform which is the highest popular mobile terminal operating system.This article first briefly describes the architecture and features of the Android platform.Then it studies the Naive Bayes classification which is one of the Bayes text classification techniques,and introduces the Chinese word segmentation and feature words chosen technology used during the text classification.Then it analyzes the business process and application needs of mobile spam messages interception system,and models the data and system process.After that the paper designs the system application architecture and the functional modules of the system,and it achieves a spam messages interception system based on Naive Bayes text classification algorithm combining with Android platform development technology.The system has many major functions such as SMS monitoring,white and black lists,message filtering,spam messages intercepting and so on.In addition,the system has a simple user interface,which is user-friendly.Finally,the paper deploys environment and tests the various functions of the system with several sets of test sample messages in a real machine.Testing the spam messages interceptor system shows that the system can perform real-time monitoring on mobile phones and it achieves intelligently blocking spam messages by classifying and filtering the contents of coming text messages.However,due to the incompleteness of the system data dictionary and limitations of the Naive Bayes classification algorithm,the system still appears errors in the classification of messages,leading to some error interception.