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摘要随着信息技术的不断发展，抄袭正变得越来越容易和难以防范。作业环节是整个教学过程中的一个重要的环节，然而作业抄袭是作业环节的一种普遍现象，许多学生为了省事、方便，常常以其他同学的作业或者网络文档为模板，简单地做少量修改，甚至不做修改就交给老师，企图蒙混过关。设计一个即方便又快速的抄袭检测系统，解除老师检查学生作业的繁重工作就很有必要。
作业抄袭检测系统采用空间向量模型和TF-IDF算法计算作业的相似性，由教师提供作业库，需检测的作业与作业库中的作业进行相似度计算，相似度超过阈值的系统自动标注指出抄袭的句子并拒绝该作业接收进作业库中，否则，将检测的作业加入作业库中。系统由C#实现人机交互界面，能够比较快速准确地完成作业检测，较好地满足教师的需求。62977
毕业论文关键词：作业；空间向量模型；TF-IDF算法；阈值；作业库
毕业设计说明书（论文）外文摘要
Title Design and implementation of the plagiarism detection system
Abstract With the continuous development of information technology, plagiarism is becoming more and more easy and difficult to prevent. Homework link is an important part in the whole teaching process, but homework is copying homework link of a common phenomenon, many students in order to save trouble, convenient, and often assignments with other students or web documents as template, simply do a small amount of change, even without modification to the teacher, tried to muddle through. To design a convenient and rapid plagiarism detection system, remove the teacher check the student work hard work is very necessary.
Electronic plagiarism detection system uses the vector space model and TF - IDF algorithm similarity computing jobs, libraries provided by the teacher homework, assignments and homework in the library of examinations should be homework for similarity calculation, the similarity is more than threshold value automatic tagging system is pointed out that the sentences of plagiarism and refuse the job receiving into his homework in the library, otherwise, will detect the electronic homework homework in the library. System consists of c # realize the human-computer interaction interface, can finish my homework more quickly and accurately detection, better meet the needs of teachers.
Keywords Homework; Vector space model; TF-IDF algorithm; Threshold value; Electronic homework library
1 绪 论 1
1.1 课题研究的背景和意义 1
1.2 国内外研究状况和发展趋势 1
1.3 论文组织结构 3
2 现有抄袭检测方法的概述 4
2.1 抄袭与剽窃的定义 4
2.2 抄袭手段的遏制方法 4
2.3 现有的抄袭技术 4
2.4 本章小结 6
3 系统的需求分析 6
3.1 应用需求分析 6
3.2 功能需求分析 7
4 系统的技术与方法 7
4.1 向量空间模型 8
4.2 特征项的选择
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