Write a paragraph of classification and example with approxi
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Write a paragraph of classification and example with approximately 150 words on the following topic:The Movies I Like.就是让我们写一篇大约150字分类例子的英文作文,主题是我喜欢的电影!
Title:
System for estimating a distribution of message content categories in source data
United States Patent Application 20090030862 Kind Code: A1
Abstract:
A method of computerized content analysis that gives “approximately unbiased and statistically consistent estimates” of a distribution of elements of structured, unstructured, and partially structured source data among a set of categories. In one embodiment, this is done by analyzing a distribution of small set of individually-classified elements in a plurality of categories and then using the information determined from the analysis to extrapolate a distribution in a larger population set. This extrapolation is performed without constraining the distribution of the unlabeled elements to be equal to the distribution of labeled elements, nor constraining a content distribution of content of elements in the labeled set (e.g., a distribution of words used by elements in the labeled set) to be equal to a content distribution of elements in the unlabeled set. Not being constrained in these ways allows the estimation techniques described herein to provide distinct advantages over conventional aggregation techniques. 再答: 如果不采纳都对不起我的辛苦
再问: 谢谢你啊!
再问: 非常感谢,我会好好参考的
System for estimating a distribution of message content categories in source data
United States Patent Application 20090030862 Kind Code: A1
Abstract:
A method of computerized content analysis that gives “approximately unbiased and statistically consistent estimates” of a distribution of elements of structured, unstructured, and partially structured source data among a set of categories. In one embodiment, this is done by analyzing a distribution of small set of individually-classified elements in a plurality of categories and then using the information determined from the analysis to extrapolate a distribution in a larger population set. This extrapolation is performed without constraining the distribution of the unlabeled elements to be equal to the distribution of labeled elements, nor constraining a content distribution of content of elements in the labeled set (e.g., a distribution of words used by elements in the labeled set) to be equal to a content distribution of elements in the unlabeled set. Not being constrained in these ways allows the estimation techniques described herein to provide distinct advantages over conventional aggregation techniques. 再答: 如果不采纳都对不起我的辛苦
再问: 谢谢你啊!
再问: 非常感谢,我会好好参考的
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