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Research on Network Information Filtering Model Based on Genetic Taboo Algorithm

Author: JiangPeiPei
Tutor: LiuPeiYu
School: Shandong Normal University
Course: Computer Software and Theory
Keywords: Network Information Filtering Genetic algorithm and tabu Naive Bayes Lexical analysis Text Summary
CLC: TP393.09
Type: Master's thesis
Year: 2011
Downloads: 50
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Abstract


With the development and application of Internet, the rapid growth of online information, rich in content and variety. However, the network is a double-edged sword, bringing convenience to mankind at the same time it is inevitably exposed to a lot of bad information; addition, based on the inherent network itself open, dynamic and heterogeneous, difficult for users obtain the required information quickly and accurately, how to automate the flow of information extracted from the dynamic to meet the information needs of individual users has become extremely important. To solve these problems, the network information filtering technology came into being. Information filtering technology can extract information based on user demand and to shield bad information, it is mainly research network access to information and said user templates to build, pending classification of the document and other issues. This article covers the various stages of information filtering, information filtering model of precision and recall two technical indicators as a starting point, do the following aspects of work: an in-depth study of the network information filtering model and its associated filter the key technology of the typical information filtering model and related algorithms, focuses on the information filtering network involved in data acquisition, word segmentation, feature selection algorithm, weight calculation, text representation model, classification algorithms and other key technologies. 2 is proposed based on genetic algorithm and tabu network information filtering model discussed in depth the basic principles of genetic algorithm and its application in the full analysis of the advantages of genetic algorithm based on genetic algorithm for the existence of the \the introduction of \In the classification stage filtering model, the model used for the conventional Bayesian classification algorithm can not solve the problem of single-class vocabulary, text to improve it, so that it has better robustness and adaptability. 3, the proposed combination of the application vocabulary sentences extracted text summarization method a text often contain a lot of sentences, but some sentences can not express the theme of the text, these redundant sentences affect genetic quality training user template form. Text abstract as an information compression tool can compress the contents of the text, to remove redundant sentences, the extracted contents of the most refined. To further improve the quality of the template, text summarization method introduced in the text corpus for optimization. Process for the removal of sub-word lexical analysis system features precision too low and cause problems between items missing semantics that the proposed amendments under the rules formulated speech, and so the rules for word after the sentence to regulate thoughts, so that the sentence semantic Words to establish the corresponding relationship ties improved method of removal of the contents of the summary is more refined and more accurate. 4, designed and implemented based on genetic algorithm and tabu network information filtering model first used in the system improved the training corpus text summarization method pretreatment; then use the genetic algorithm and tabu training text, the formation of the optimal user template; Finally, the improved classification algorithm to classify text to be measured, and ultimately achieve a multi-level, multi-strategy and modular network based on genetic algorithm and tabu information filtering system. After testing, the system is reliable, stable and efficient, able to network information for effective filtration.

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CLC: > Industrial Technology > Automation technology,computer technology > Computing technology,computer technology > Computer applications > Computer network > General issues > The application of computer network
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