Cloud-based plagiarism detection system performing predicting based on classified feature vectors
    1.
    发明授权
    Cloud-based plagiarism detection system performing predicting based on classified feature vectors 有权
    基于分类特征向量执行预测的云剽窃检测系统

    公开(公告)号:US09514417B2

    公开(公告)日:2016-12-06

    申请号:US14143710

    申请日:2013-12-30

    Applicant: Google Inc.

    CPC classification number: G06N99/005 G06F17/30011 G06Q10/107

    Abstract: Plagiarism may be detected, as disclosed herein, utilizing a database that stores documents for one or more courses. The database may restrict sharing of content between documents. A feature extraction module may receive edits and timestamp the edits to the document. A writing pattern for a particular user or group of users may be discerned from the temporal data and the documents for the particular user or group of users. A feature vector may be generated that represents the writing pattern. A machine learning technique may be applied to the feature vector to determine whether or not a document is plagiarized.

    Abstract translation: 可以如本文所公开的那样利用存储用于一个或多个课程的文档的数据库来检测抄袭。 数据库可能限制文档之间的内容共享。 特征提取模块可以接收对文档的编辑和时间戳。 可以从特定用户或用户组的时间数据和文档中辨别特定用户或用户组的写入模式。 可以生成表示写入模式的特征向量。 可以将机器学习技术应用于特征向量以确定文档是否被剽窃。

    Cloud-based plagiarism detection system
    2.
    发明申请
    Cloud-based plagiarism detection system 有权
    基于云的剽窃检测系统

    公开(公告)号:US20150186787A1

    公开(公告)日:2015-07-02

    申请号:US14143710

    申请日:2013-12-30

    Applicant: Google Inc.

    CPC classification number: G06N99/005 G06F17/30011 G06Q10/107

    Abstract: Plagiarism may be detected, as disclosed herein, utilizing a database that stores documents for one or more courses. The database may restrict sharing of content between documents. A feature extraction module may receive edits and timestamp the edits to the document. A writing pattern for a particular user or group of users may be discerned from the temporal data and the documents for the particular user or group of users. A feature vector may be generated that represents the writing pattern. A machine learning technique may be applied to the feature vector to determine whether or not a document is plagiarized.

    Abstract translation: 可以如本文所公开的那样利用存储用于一个或多个课程的文档的数据库来检测抄袭。 数据库可能限制文档之间的内容共享。 特征提取模块可以接收对文档的编辑和时间戳。 可以从特定用户或用户组的时间数据和文档中辨别特定用户或用户组的写入模式。 可以生成表示写入模式的特征向量。 可以将机器学习技术应用于特征向量以确定文档是否被剽窃。

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