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    Mining Suspicious Tax Evasion Groups In Big Data project in Jakarta Servlet ( formerly Java Servlet ) with source code and document.

    Jakarta Servlet ( formerly Java Servlet ) project   Last updated on - July 12, 2018
    vino vasanth
    vino vasanth
    hadoop java php web development 
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    In this page Mining Suspicious Tax Evasion Groups In Big Data project is a desktop application which is developed in Jakarta Servlet ( formerly Java Servlet ) platform. This Jakarta Servlet ( formerly Java Servlet ) project with tutorial and guide for developing a code. Mining Suspicious Tax Evasion Groups In Big Data is a open source you can Download zip and edit as per you need. If you want more latest Jakarta Servlet ( formerly Java Servlet ) projects here. This is simple and basic level small project for learning purpose. Also you can modified this system as per your requriments and develop a perfect advance level project. Zip file containing the source code that can be extracted and then imported into Eclipse. Here Project Source code for BE, BTech, MCA, BCA, Engineering, Bs.CS, IT, Software Engineering, Computer Science students and Devloper. Student can submit in college for final year project. This script developed by vino vasanth. This desktop application 100% working smooth without any bug. It is developed using java,hadoop and Database hdfs. This software code helpful in academic projects and research paper for final year computer science. You can explore great collection of other Jakarta Servlet ( formerly Java Servlet ) projects.

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    About Mining Suspicious Tax Evasion Groups In Big Data project

    project Name

    Mining Suspicious Tax Evasion Groups In Big Data

    Project Complexityadvanced
    Duration15 Days
    project ID2443
    Developer Namevino vasanth
    Publish DateJuly 12, 2018
    project PlatformJakarta Servlet ( formerly Java Servlet )
    Programming Languagejava,hadoop
    Front End
    Back End
    IDE ToolEclipse
    Database Integrationhdfs
    project Typedesktop Application
    No of project Download91
    project Total View3404
    Today Trends1
    Current Month Trends40
    Last Month Trends38

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    Features and function of the Mining Suspicious Tax Evasion Groups In Big Data project

    There is evidence that an increasing number of enterprises plot together to evade tax in an unperceived way. At the same time, the taxation information related data is a classic kind of big data. The issues challenge the effectiveness of traditional data mining-based tax evasion detection methods. To address this problem, we first investigate the classic tax evasion cases, and employ a graph-based method to characterize their property that describes two suspicious relationship trails with a same antecedent node behind an Interest Affiliated Transaction (IAT). Next, we propose a colored network-based model (CNBM) for characterizing economic behaviors, social relationships and the IATs between taxpayers, and generating a Taxpayer Interest Interacted Network (TPIIN). To accomplish the tax evasion detection task by discovering suspicious groups in a TPIIN, methods for building a patterns tree and matching component patterns are introduced and the completeness of the methods based on graph theory is presented. Then, we describe an experiment based on real data and a simulated network. The experimental results show that our proposed method greatly improves the efficiency of tax evasion detection, as well as provides a clear explanation of the tax evasion behaviors of taxpayer groups.

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    Download Mining Suspicious Tax Evasion Groups In Big Data source code

    Download Mining Suspicious Tax Evasion Groups In Big Data source code at free of cost. Download link provide below.

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    File size 3.3113 MB

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