首页> 外国专利> Regularized Iterative Collaborative Feature Learning From Web and User Behavior Data

Regularized Iterative Collaborative Feature Learning From Web and User Behavior Data

机译:基于Web和用户行为数据的正则化迭代协作特征学习

摘要

Certain embodiments involve learning features of content items (e.g., images) based on web data and user behavior data. For example, a system determines latent factors from the content items based on data including a user's text query or keyword query for a content item and the user's interaction with the content items based on the query (e.g., a user's click on a content item resulting from a search using the text query). The system uses the latent factors to learn features of the content items. The system uses a previously learned feature of the content items for iterating the process of learning features of the content items to learn additional features of the content items, which improves the accuracy with which the system is used to learn other features of the content items.
机译:某些实施例涉及基于网络数据和用户行为数据的内容项(例如,图像)的学习特征。例如,系统基于数据来从内容项目中确定潜在因素,这些数据包括用户对内容项目的文本查询或关键字查询,以及基于查询的用户与内容项目的交互(例如,用户对内容项目产生的点击)来自使用文本查询的搜索)。系统使用潜在因素来学习内容项的特征。系统使用内容项的先前学习的特征来迭代学习内容项的特征的过程以学习内容项的附加特征,这提高了系统用于学习内容项的其他特征的准确性。

著录项

相似文献

  • 专利
  • 外文文献
  • 中文文献
获取专利

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号