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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 
2 Reviews
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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.

Document and reports information of Mining Suspicious Tax Evasion Groups In Big Data

This doucment file contains project Synopsis, Reports, and various diagrams. Also Abstract in PDF, PPT file inside zip so that document link below the page. UML diagrams for Mining Suspicious Tax Evasion Groups In Big Data. Class diagrams, Use Case diagrams, Entity–relationship(ER) diagrams, Data flow diagram(DFD), Sequence diagram and software requirements specification (SRS) in report file. Complete ready made open source code free of cost download. You can find Top Downloaded Jakarta Servlet ( formerly Java Servlet ) projects here.

About Mining Suspicious Tax Evasion Groups In Big Data project

project Name

Mining Suspicious Tax Evasion Groups In Big Data

project ID2443
Developer Namevino vasanth
Publish DateJuly 12, 2018
project PlatformJakarta Servlet ( formerly Java Servlet )
Programming Languagejava,hadoop
Front End
Back End
IDE ToolEclipse
Databasehdfs
project Typedesktop Application
No of project Download90
project Total View3162
Today Trends2
Current Month Trends40
Last Month Trends30

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File size 3.3113 MB

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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.

User modules and function of Mining Suspicious Tax Evasion Groups In Big Data

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