本文關(guān)鍵詞：數(shù)據(jù)挖掘技術(shù)在刑事案件信息分析中的應(yīng)用　出處：《西安電子科技大學(xué)》2011年碩士論文　論文類(lèi)型：學(xué)位論文

  更多相關(guān)文章： 數(shù)據(jù)挖掘 關(guān)聯(lián)規(guī)則 Apriori算法 ID3算法 決策樹(shù)

【摘要】：隨著“金盾工程”的建設(shè)和應(yīng)用，各級(jí)公安機(jī)關(guān)業(yè)務(wù)系統(tǒng)積累了大量的刑事案件原始數(shù)據(jù)信息。如何采用信息技術(shù)，發(fā)現(xiàn)更多數(shù)據(jù)中隱藏的犯罪規(guī)律，以期提高公安機(jī)關(guān)打擊偵破犯罪的水平，成為一個(gè)極具現(xiàn)實(shí)意義的課題。 本文基于數(shù)據(jù)挖掘技術(shù),結(jié)合SQL Server2000數(shù)據(jù)庫(kù),通過(guò)數(shù)據(jù)清洗、概化及連續(xù)屬性離散化把大量不適用挖掘的數(shù)據(jù)轉(zhuǎn)化為適用挖掘的數(shù)據(jù)，首先解決了數(shù)據(jù)預(yù)處理問(wèn)題；然后基于關(guān)聯(lián)規(guī)則,重點(diǎn)研究了Aprior算法的改進(jìn)，通過(guò)對(duì)剪枝和連接步的優(yōu)化，有效提高了算法運(yùn)行效率，分析兵團(tuán)某師近三年的刑事案件數(shù)據(jù)記錄，，得出頻繁項(xiàng)集，導(dǎo)出關(guān)聯(lián)規(guī)則，分析了案件類(lèi)別與犯罪嫌疑人年齡、職業(yè)、戶籍、文化程度等因素之間的關(guān)聯(lián)關(guān)系；運(yùn)用ID3算法，基于信息增益，構(gòu)建了以案件類(lèi)別為核心的犯罪分析決策樹(shù)，并對(duì)模型進(jìn)行了解釋評(píng)估；最后設(shè)計(jì)開(kāi)發(fā)出一個(gè)小型仿真刑事案件信息分析系統(tǒng)，驗(yàn)證了算法實(shí)現(xiàn)，為數(shù)據(jù)挖掘關(guān)聯(lián)規(guī)則技術(shù)在地區(qū)公安信息分析中的應(yīng)用提供了新思路，并拓展了該技術(shù)的使用范圍。
[Abstract]:With the construction and application of the "Golden Shield Project", the operational system of public security organs at all levels has accumulated a large amount of original data information on criminal cases. How to use information technology to discover the hidden laws of crime in more data. In order to improve the level of public security organs to crack down on crime, become a very practical significance of the subject. This paper is based on data mining technology, combined with SQL Server2000 database, through data cleaning. Generalizability and continuous attribute discretization transform a large amount of unsuitable mining data into suitable mining data. Firstly, the problem of data preprocessing is solved. Then based on the association rules, the paper focuses on the improvement of Aprior algorithm. Through the optimization of pruning and linking steps, it effectively improves the efficiency of the algorithm, and analyzes the criminal case data records of a certain division of the Corps in the past three years. The frequent itemsets are obtained, the association rules are derived, and the correlation relationship between the category of cases and the age, occupation, household registration and education level of the criminal suspects is analyzed. Using ID3 algorithm, based on information gain, a crime analysis decision tree with case category as the core is constructed, and the model is interpreted and evaluated. Finally, a small simulation criminal case information analysis system is designed and developed, which verifies the implementation of the algorithm, and provides a new idea for the application of data mining association rule technology in regional public security information analysis. The application scope of the technology is expanded.
【學(xué)位授予單位】：西安電子科技大學(xué)
【學(xué)位級(jí)別】：碩士
【學(xué)位授予年份】：2011
【分類(lèi)號(hào)】：D918;TP311.13

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