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Systems and methods of predicting resource usefulness using universal resource locators including counting the number of times URL features occur in training data

机译:使用通用资源定位器预测资源有用性的系统和方法,包括计算URL特征在训练数据中出现的次数

摘要

A method, system and apparatus are provided to train a usefulness prediction model to generate a usefulness prediction in connection with a given universal resource locator (URL), the training of the usefulness prediction model being based on a training set of URLs and a count of negative URLs and a count of positive URLs identified by the training set, and for each feature extacted from the URLs in the training set, a count of the positive URLs in the training set that include the feature and a count of the negative URLs in the training set that include the feature. One or more features of the given URL are extracted, and the extracted features are used together with the usefulness prediction model to generate a usefulness prediction for the given URL.
机译:提供了一种方法,系统和装置,用于训练有用性预测模型以结合给定的通用资源定位符(URL)来生成有用性预测,该有用性预测模型的训练基于URL的训练集和否定URL和由训练集标识的肯定URL的数量,对于从训练集中的URL扩展而来的每个功能,在训练集中包含该功能的肯定URL的数量以及在训练集中确定的否定URL的数量包含该功能的训练集。提取给定URL的一个或多个特征,并将提取的特征与有用性预测模型一起使用以生成给定URL的有用性预测。

著录项

  • 公开/公告号US7908234B2

    专利类型

  • 公开/公告日2011-03-15

    原文格式PDF

  • 申请/专利权人 ZHENG SHAO;WENJIE FU;

    申请/专利号US20080032111

  • 发明设计人 ZHENG SHAO;WENJIE FU;

    申请日2008-02-15

  • 分类号G06E1/00;

  • 国家 US

  • 入库时间 2022-08-21 18:09:07

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