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Research on Content-based Short Message Intelligent Analysis System

Author: HouXuDong
Tutor: ZhangJing
School: Chongqing University of Technology
Course: Signal and Information Processing
Keywords: SMS Content-based Naive Bayes Support Vector Machine Text Classification
CLC: TN929.5
Type: Master's thesis
Year: 2010
Downloads: 32
Quote: 0
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Abstract


In recent years , a growing problem of spam messages , resulting in a significant negative impact not only to the telecom operators , but also to the entire society . Telecom operators , have introduced a variety of spam filtering system to govern the proliferation of spam messages . Mainly spam messages determination method includes : sending flow determination , content keywords are determined and judged according to the called party number features . Although these methods governance of the spam messages have a certain effect , but there are also obvious defects and deficiencies . In this paper , existing SMS filtering technology deficiencies , in -depth analysis on the basis of the original filtration technology , semantic intelligent analysis of the short message content - based approach to determine the spam messages , this paper is mainly to complete the work and innovation including the following aspects: 1 . explore the research status of the spam filtering problem , summed operators spam messages to determine the mechanism of its pros and cons . Designed a content-based Message intelligent analysis system , to develop the overall structure of the system , a process flow of the main function of each module and system . 3 . Flow threshold analysis , the keyword processing and content intelligence analysis of three major functional modules, and put forward a specific time backtracking algorithms, statistical user to send spam short message flow . 4 . A Naive Bayes algorithm combining support vector machine classification algorithm . Naive Bayesian method has a fast , high efficiency , and can be used for online classifieds . And the support vector machine classification accuracy is high , but in the face of large - scale short message text , slow convergence for offline classification , and feedback , update the SMS feature samples library . Experiments show that compared to traditional methods , using the improved algorithm design , intelligent analysis of the short message system , succeeded in raising short messages classified intelligence , reliability , timeliness and the accuracy rate . In this paper, the intelligent analysis system based on short message SMS filtering system improvement and perfection of an intelligent , has a very broad application prospect .

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