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    • 3. 发明授权
    • Indexing semantic user profiles for targeted advertising
    • 索引用于定向广告的语义用户配置文件
    • US08533188B2
    • 2013-09-10
    • US13235140
    • 2011-09-16
    • Jun YanNing LiuLei JiSteven J. HanksQing XuZheng Chen
    • Jun YanNing LiuLei JiSteven J. HanksQing XuZheng Chen
    • G06F17/30
    • G06F17/30321G06F17/30867
    • Embodiments facilitate greater flexibility in definition of user segments for targeted advertising, by employing indexed semantic user profiles. Semantic user profiles are built through extraction of online user behavior data such as user search queries and page views, and include user interest information that is inferred based on user behavior. Semantic user profiles are then indexed to facilitate search for a set of users that fit specified semantic search terms. Search results for semantic profiles are ranked according to a ranking model developed through machine learning. In some embodiments, building and indexing of semantic profiles and learning of the ranking model is performed offline to facilitate more efficient online processing of queries.
    • 实施例通过采用索引语义用户简档来促进用于定向广告的用户段的定义的更大的灵活性。 通过提取在线用户行为数据(如用户搜索查询和页面浏览)构建语义用户配置文件,并包括基于用户行为推断的用户兴趣信息。 然后索引语义用户简档,以便于搜索适合指定语义搜索术语的一组用户。 根据通过机器学习开发的排名模型对语义轮廓的搜索结果进行排名。 在一些实施例中,离线地执行语义概况的构建和索引以及排名模型的学习,以便更有效地在线处理查询。
    • 4. 发明申请
    • Indexing Semantic User Profiles for Targeted Advertising
    • 索引目标广告的语义用户个人资料
    • US20130073546A1
    • 2013-03-21
    • US13235140
    • 2011-09-16
    • Jun YanNing LiuLei JiSteven J. HanksQing XuZheng Chen
    • Jun YanNing LiuLei JiSteven J. HanksQing XuZheng Chen
    • G06F17/30
    • G06F17/30321G06F17/30867
    • Embodiments facilitate greater flexibility in definition of user segments for targeted advertising, by employing indexed semantic user profiles. Semantic user profiles are built through extraction of online user behavior data such as user search queries and page views, and include user interest information that is inferred based on user behavior. Semantic user profiles are then indexed to facilitate search for a set of users that fit specified semantic search terms. Search results for semantic profiles are ranked according to a ranking model developed through machine learning. In some embodiments, building and indexing of semantic profiles and learning of the ranking model is performed offline to facilitate more efficient online processing of queries.
    • 实施例通过采用索引语义用户简档来促进用于定向广告的用户段的定义的更大的灵活性。 通过提取在线用户行为数据(如用户搜索查询和页面浏览)构建语义用户配置文件,并包括基于用户行为推断的用户兴趣信息。 然后索引语义用户简档,以便于搜索适合指定语义搜索术语的一组用户。 根据通过机器学习开发的排名模型对语义轮廓的搜索结果进行排名。 在一些实施例中,离线地执行语义概况的构建和索引以及排名模型的学习,以便更有效地在线处理查询。