-
公开(公告)号:US20140019857A1
公开(公告)日:2014-01-16
申请号:US13565360
申请日:2012-08-02
IPC分类号: G06F17/24
摘要: An embodiment of the invention directed to a method is associated with data content, comprising discrete data portions including first data and second data portions separated from each other in the data content. A copy operation is implemented on data portions so that at least some of the data portions are each copied to a buffer, which include the first and second data portions. A paste operation is carried out to present each of the copied data portions as an input for an output data selection task. Prespecified criteria is used in the output data selection task to select a number of the copied data portions to be selected data for a given purpose, the selected number of copied data portions being less than data portions presented by the paste operation, and the selected copied data portions including the first and second data portions.
摘要翻译: 涉及一种方法的本发明的实施例与数据内容相关联,包括离散数据部分,其包括在数据内容中彼此分离的第一数据和第二数据部分。 在数据部分上实现复制操作,使得至少一些数据部分被复制到包括第一和第二数据部分的缓冲器中。 执行粘贴操作以将每个复制数据部分呈现为输出数据选择任务的输入。 在输出数据选择任务中使用预定标准来选择用于给定目的的要被选择数据的复制数据部分的数量,所选择的复制数据部分数量小于通过粘贴操作呈现的数据部分,并且所选择的复制 数据部分包括第一和第二数据部分。
-
公开(公告)号:US08566270B2
公开(公告)日:2013-10-22
申请号:US13242145
申请日:2011-09-23
CPC分类号: G06F17/2715 , G06F17/30707
摘要: A sparse representation method of text classification is described. An input text document is represented as a document feature vector y. A category dictionary H provides possible examples [h1; h2; . . . ; hn] of the document feature vector y. The input text document is classified using a sparse representation text classification algorithm that solves for y=Hβ where a sparseness condition is enforced on β to select a small number of examples from the dictionary H to describe the document feature vector y.
摘要翻译: 描述了文本分类的稀疏表示方法。 输入文本文档表示为文档特征向量y。 类别字典H提供了可能的例子[h1; h2; 。 。 。 ; hn]的文档特征向量y。 输入文本文档使用稀疏表示文本分类算法进行分类,该算法解决了y = Hbeta,其中在beta上执行稀疏条件以从字典H中选择少量示例来描述文档特征向量y。
-
公开(公告)号:US20120078834A1
公开(公告)日:2012-03-29
申请号:US13242145
申请日:2011-09-23
IPC分类号: G06N5/02
CPC分类号: G06F17/2715 , G06F17/30707
摘要: A sparse representation method of text classification is described. An input text document is represented as a document feature vector y. A category dictionary H provides possible examples [h1; h2; . . . ; hn] of the document feature vector y. The input text document is classified using a sparse representation text classification algorithm that solves for y=Hβ where a sparseness condition is enforced on β to select a small number of examples from the dictionary H to describe the document feature vector y.
摘要翻译: 描述了文本分类的稀疏表示方法。 输入文本文档表示为文档特征向量y。 类别字典H提供了可能的例子[h1; h2; 。 。 。 ; hn]的文档特征向量y。 输入文本文档使用解决y = H&bgr的稀疏表示文本分类算法进行分类; 在“bgr”上执行稀疏条件 从字典H中选择少量示例来描述文档特征向量y。
-
-