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    • 5. 发明申请
    • Automatic Classification of Search Engine Quality
    • 搜索引擎质量的自动分类
    • US20090327224A1
    • 2009-12-31
    • US12146813
    • 2008-06-26
    • Ryen William WhiteMikhail BilenkoMatthew R. Richardson
    • Ryen William WhiteMikhail BilenkoMatthew R. Richardson
    • G06F17/30
    • G06F16/951
    • Aspects of the subject matter described herein relate to predicting a best search engine to use for a given query. In aspects, a predictor may use various approaches to determine a best search engine for a given query. For example, the predictor may use features derived from the query itself, how well the query matches a result set returned by a search engine in response to the query, and/or information that compares the result sets returned by multiple search engines that are provided the query. In addition, other data such as user preferences, user interaction data, metadata attributes, and/or other data may be used in predicting a best search engine for a given query. In conjunction with making a prediction, the predictor may use a classifier that has been trained at a training facility.
    • 本文描述的主题的方面涉及预测用于给定查询的最佳搜索引擎。 在方面,预测器可以使用各种方法来确定给定查询的最佳搜索引擎。 例如,预测器可以使用从查询本身导出的特征,查询与搜索引擎响应于查询返回的结果集匹配的程度以及/或比较由多个搜索引擎返回的结果集的信息 查询。 此外,可以使用诸如用户偏好,用户交互数据,元数据属性和/或其他数据的其他数据来预测给定查询的最佳搜索引擎。 结合预测,预测器可以使用已经在训练设施训练的分类器。
    • 6. 发明申请
    • Exploratory Search Technique
    • 探索性搜索技术
    • US20080319975A1
    • 2008-12-25
    • US11767142
    • 2007-06-22
    • Daniel Scott MorrisMeredith June MorrisGina Danielle VenoliaRyen William WhiteEric HorvitzSteven M. Drucker
    • Daniel Scott MorrisMeredith June MorrisGina Danielle VenoliaRyen William WhiteEric HorvitzSteven M. Drucker
    • G06F17/30
    • G06F3/048G06F16/951G06F2203/04803
    • A technique for the creation of synthesized results from multi-query searches to provide more relevant information to the user in a more useful format and to discard or reduce in relevancy information that is not so useful. It allows a user to define the boundaries of the exploratory search before it starts or retroactively define which queries belong to the search. It can imply which queries belong to the search based on parameters in the queries or results. It also provides mechanisms for supporting exploratory searches including: saving/restoring search context; search-specific query history; a “keepers” bin for storing useful results; elimination of redundant results; re-ranking of common search results; integration of searching with navigation; pivoting on search results; collaboration among multiple searchers; user-generated content; generation of hypotheses; re-executing queries and executing standing queries; multi-monitor searching and automatic preparation of search summaries. User interfaces for conducting multi-query searches are also provided.
    • 一种用于从多查询搜索创建合成结果的技术,以更有用的格式向用户提供更多的相关信息,并丢弃或减少不那么有用的相关性信息。 它允许用户在开始之前定义探索性搜索的边界,或者追溯地定义哪些查询属于搜索。 它可以暗示哪些查询属于基于查询或结果中的参数的搜索。 它还提供支持探索性搜索的机制,包括:保存/恢复搜索环境; 搜索专用查询记录; 用于存储有用结果的“管理员”仓; 消除冗余结果; 共同搜索结果重新排序; 搜索与导航的整合; 在搜索结果上转动; 多个搜索者之间的协作; 用户生成内容; 一代假设; 重新执行查询并执行常规查询; 多监视搜索和自动准备搜索摘要。 还提供了用于进行多查询搜索的用户界面。
    • 8. 发明申请
    • RANKING SEARCH RESULTS USING RESULT REPETITION
    • 使用结果重复排列搜索结果
    • US20130246412A1
    • 2013-09-19
    • US13420591
    • 2012-03-14
    • Milad ShokouhiRyen William WhitePaul Nathan Bennett
    • Milad ShokouhiRyen William WhitePaul Nathan Bennett
    • G06F17/30
    • G06F17/30867
    • Ranking search results using result repetition is described. In an embodiment, a set of results generated by a search engine is ranked or re-ranked based on whether any of the results were included in previous sets of results generated in response to earlier queries by the same user in one or more searching sessions. User behavior data, such as whether a user clicks on a result, skips a result or misses a result, is stored in real-time and the stored data is used in performing the ranking. In various examples, the ranking is performed using a machine-learning algorithm and various parameters, such as whether a result in a current set of results has previously been clicked, skipped or missed in the same session, are generated based on the user behavior data for the current session and input to the machine-learning algorithm.
    • 描述使用结果重复排列搜索结果。 在一个实施例中,基于是否将任何结果包括在响应于同一用户在一个或多个搜索会话中的较早查询而生成的先前的结果集合中来对搜索引擎生成的一组结果进行排名或重新排序。 实时存储用户行为数据,例如用户是否点击结果,跳过结果或丢失结果,并且存储的数据用于执行排名。 在各种示例中,使用机器学习算法执行排名,并且基于用户行为数据生成各种参数,诸如是否先前在同一会话中点击,跳过或丢失了当前结果集中的结果 为当前会话并输入到机器学习算法。
    • 9. 发明授权
    • Identification and use of web searcher expertise
    • 识别和使用网络搜索专家
    • US07996400B2
    • 2011-08-09
    • US11767489
    • 2007-06-23
    • Daniel Scott MorrisRyen William White
    • Daniel Scott MorrisRyen William White
    • G06F7/00G06F17/30
    • G06F17/30867
    • A search expertise level system and method for determining a search expertise level of a search engine user and then using that information to improve the searcher's experience. The search expertise level system and method identifies the search expertise level of the searcher based on query behavior, post-query browsing behavior, and other behaviors of the searcher. One simple and important behavior that indicates a skilled searcher is the use of advanced query syntax and operators in the query. Once the search expertise level of a searcher is known, the search engine user interface can be modified and tailored to the needs of both skilled and novice searchers. The search expertise level also can be used to rank search results, such that search results for a novice searcher are ranked differently than those for a skilled searcher. The search expertise level also can be used in advertising and marketing.
    • 用于确定搜索引擎用户的搜索专长级别,然后使用该信息来提高搜索者体验的搜索专业级别系统和方法。 搜索专家级别系统和方法基于查询行为,查询后浏览行为和搜索者的其他行为来识别搜索者的搜索专业级别。 指示熟练的搜索者的一个简单且重要的行为是在查询中使用高级查询语法和运算符。 一旦知道搜索者的搜索专长级别,搜索引擎用户界面可以根据熟练和新手搜索者的需要进行修改和调整。 搜索专家级别还可以用于对搜索结果进行排名,使得新手搜索者的搜索结果的排名与技术搜索者的搜索结果不同。 搜索专业水平也可用于广告和营销。