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1. 发明授权

US07885986B2 Enhanced browsing experience in social bookmarking based on self tags 有权
标题翻译：增强基于自我标签的社交书签浏览体验
公开(公告)号：US07885986B2
公开(公告)日：2011-02-08
申请号：US11769146
申请日：2007-06-27
申请人： Brigham Anderson , David M. Chickering
发明人： Brigham Anderson , David M. Chickering
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06F17/30884 , G06Q10/10 , G06Q30/02
摘要： Improved browsing experience in social bookmarking by leveraging aspects of self tagging and prediction. Quality recommendations are provided for sites of interest to the user and information about what types of people like the current website. Self-tagging is used as an effective means to perform personalized searches. Machine learning and reasoning is employed to predict self-tags based on a website visited and/or website behavior, and self-tags associated with a website and/or webpage based on content of that website and/or webpage. The architecture can be embodied as a browser utility to leverage and extend social-bookmarking information. The utility facilitates the display of information related to a summary view of the users who liked/disliked the current page or website, a tag cloud associated with webpages, and a recommendation button that causes self-tag recommendations to be displayed and that recommends links based on the combination of user tags and content.
摘要翻译：通过利用自我标记和预测的方面，改善了社会书签的浏览体验。为用户感兴趣的网站提供质量建议，以及关于什么类型的人像当前网站的信息。自我标记被用作执行个性化搜索的有效手段。采用机器学习和推理来基于所访问的网站和/或网站行为来预测自标签，以及基于该网站和/或网页的内容与网站和/或网页相关联的自标签。该架构可以体现为浏览器实用程序，以利用和扩展社会书签信息。该实用程序有助于显示与喜欢/不喜欢当前页面或网站的用户的摘要视图相关联的信息，与网页相关联的标签云以及引起自标签建议被显示的推荐按钮，并且推荐基于链接关于用户标签和内容的组合。

2. 发明申请

US20090006442A1 ENHANCED BROWSING EXPERIENCE IN SOCIAL BOOKMARKING BASED ON SELF TAGS 有权
标题翻译：基于自我标签的社会书签中的增强浏览体验
公开(公告)号：US20090006442A1
公开(公告)日：2009-01-01
申请号：US11769146
申请日：2007-06-27
申请人： Brigham Anderson , David M. Chickering
发明人： Brigham Anderson , David M. Chickering
IPC分类号： G06F7/00
CPC分类号： G06F17/30884 , G06Q10/10 , G06Q30/02
摘要： Improved browsing experience in social bookmarking by leveraging aspects of self tagging and prediction. Quality recommendations are provided for sites of interest to the user and information about what types of people like the current website. Self-tagging is used as an effective means to perform personalized searches. Machine learning and reasoning is employed to predict self-tags based on a website visited and/or website behavior, and self-tags associated with a website and/or webpage based on content of that website and/or webpage. The architecture can be embodied as a browser utility to leverage and extend social-bookmarking information. The utility facilitates the display of information related to a summary view of the users who liked/disliked the current page or website, a tag cloud associated with webpages, and a recommendation button that causes self-tag recommendations to be displayed and that recommends links based on the combination of user tags and content.
摘要翻译：通过利用自我标记和预测的方面，改善了社会书签的浏览体验。为用户感兴趣的网站提供质量建议，以及关于什么类型的人像当前网站的信息。自我标记被用作执行个性化搜索的有效手段。采用机器学习和推理来基于所访问的网站和/或网站行为来预测自标签，以及基于该网站和/或网页的内容与网站和/或网页相关联的自标签。该架构可以体现为浏览器实用程序，以利用和扩展社会书签信息。该实用程序有助于显示与喜欢/不喜欢当前页面或网站的用户的摘要视图相关联的信息，与网页相关联的标签云以及引起自标签建议被显示的推荐按钮，并且推荐基于链接关于用户标签和内容的组合。

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