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    • 11. 发明申请
    • DATA CLASSIFICATION USING MACHINE LEARNING TECHNIQUES
    • 使用机器学习技术的数据分类
    • US20110145178A1
    • 2011-06-16
    • US13033536
    • 2011-02-23
    • Mauritius A.R. SchmidtlerRoland Borrey
    • Mauritius A.R. SchmidtlerRoland Borrey
    • G06F15/18
    • G06F17/30707G06N99/005
    • A system and article of manufacture enabling adapting to a shift in document content according to one embodiment of the present invention includes instructions for: receiving at least one labeled seed document; receiving unlabeled documents; receiving at least one predetermined cost factor; training a transductive classifier using the at least one predetermined cost factor, the at least one seed document, and the unlabeled documents; classifying the unlabeled documents having a confidence level above a predefined threshold into a plurality of categories using the classifier; reclassifying at least some of the categorized documents into the categories using the classifier; and outputting identifiers of the categorized documents to at least one of a user, another system, and another process. Systems and articles of manufacture for separating documents are also presented. Systems and articles of manufacture for document searching are also presented.
    • 根据本发明的一个实施例的能够适应文档内容的移动的系统和制品包括用于:接收至少一个标记的种子文档的指令; 收到未标记的文件; 接收至少一个预定的成本因子; 使用所述至少一个预定成本因素,所述至少一个种子文档和所述未标记的文档来训练转换分类器; 使用分类器将具有高于预定义阈值的置信水平的未标记文档分类成多个类别; 使用分类器将至少一些分类文档重新分类为类别; 以及将分类文档的标识符输出到用户,另一系统和另一进程中的至少一个。 还介绍了分离文件的系统和制造。 还提供了用于文档搜索的系统和制品。