会员体验
专利管家(专利管理)
工作空间(专利管理)
风险监控(情报监控)
数据分析(专利分析)
侵权分析(诉讼无效)
联系我们
交流群
官方交流:
QQ群: 891211   
微信请扫码    >>>
现在联系顾问~
热词
    • 1. 发明授权
    • Using linear and log-linear model combinations for estimating probabilities of events
    • 使用线性和对数线性模型组合来估计事件的概率
    • US08484077B2
    • 2013-07-09
    • US12893939
    • 2010-09-29
    • Ozgur CetinEren ManavogluKannan AchanErick Cantu-PazRukmini Iyer
    • Ozgur CetinEren ManavogluKannan AchanErick Cantu-PazRukmini Iyer
    • G06Q30/00
    • G06Q30/0277G06Q10/04G06Q30/0241
    • A method for combining multiple probability of click models in an online advertising system into a combined predictive model, the method commencing by receiving a feature set slice (e.g. corresponding to demographics or taxonomies or clusters), and using the sliced data for training multiple slice-wise predictive models. The trained slice-wise predictive models are combined by overlaying a weighted distribution model over the trained slice-wise predictive models. The combined predictive model then is used in predicting the probability of a click given a query-advertisement pair in online advertising. The method can flexibly receive slice specifications, and can overlay any one or more of a variety of distribution models, such as a linear combination or a log-linear combination. Using an appropriate weighted distribution model, the combined predictive model reliably yields predictive estimates of occurrence of click events that are at least as good as the best predictive model in the slice-wise predictive model set.
    • 一种将在线广告系统中的点击模型的多种概率组合成组合预测模型的方法,该方法通过接收特征集切片(例如,对应于人口统计学或分类或群集)开始,并且使用分片数据来训练多个切片 - 明智的预测模型。 训练的切片预测模型通过在训练的切片预测模型上重叠加权分布模型来组合。 然后,组合预测模型用于预测在线广告中给予查询广告对的点击的概率。 该方法可以灵活地接收切片规格,并且可以覆盖各种分布模型中的任何一个或多个,例如线性组合或对数线性组合。 使用适当的加权分布模型,组合预测模型可靠地产生至少与切片预测模型集中的最佳预测模型一样好的点击事件发生的预测估计。
    • 3. 发明申请
    • SYSTEM AND METHOD FOR PREDICTING CONTEXT-DEPENDENT TERM IMPORTANCE OF SEARCH QUERIES
    • 用于预测搜索查询的背景相关重要性的系统和方法
    • US20110131157A1
    • 2011-06-02
    • US12626892
    • 2009-11-28
    • Rukmini IyerEren ManavogluHema Raghavan
    • Rukmini IyerEren ManavogluHema Raghavan
    • G06F17/30G06F15/18
    • G06Q30/0251
    • An improved system and method for identifying context-dependent term importance of queries is provided. A query term importance model is learned using supervised learning of context-dependent term importance for queries and is then applied for advertisement prediction using term importance weights of query terms as query features. For instance, a query term importance model for query rewriting may predict rewritten queries that match a query with term importance weights assigned as query features. Or a query term importance model for advertisement prediction may predict relevant advertisements for a query with term importance weights assigned as query features. In an embodiment, a sponsored advertisement selection engine selects sponsored advertisements scored by a query term importance engine that applies a query term importance model using term importance weights as query features and inverse document frequency weights as advertisement features to assign a relevance score.
    • 提供了一种用于识别查询的上下文相关项重要性的改进的系统和方法。 使用对查询的上下文相关项重要性的监督学习来学习查询词重要性模型,然后将其用作查询词语的重要度权重作为查询特征应用于广告预测。 例如,用于查询重写的查询项重要性模型可以预测与查询匹配的重写查询与被分配为查询特征的术语重要性权重。 或者用于广告预测的查询词重要性模型可以预测具有被指定为查询特征的术语重要性权重的查询的相关广告。 在一个实施例中,赞助的广告选择引擎选择由查询词语重要性引擎评分的赞助广告,该查询词语重要性引擎使用术语重要性权重作为查询特征和逆文档频率权重作为广告特征来分配相关性得分。
    • 6. 发明申请
    • CONTEXTUAL QUERY ADJUSTMENTS USING NATURAL ACTION INPUT
    • 使用自然行动输入进行内部查询调整
    • US20140019462A1
    • 2014-01-16
    • US13549503
    • 2012-07-15
    • Larry Paul HeckMadhusudan ChinthakuntaRukmini Iyer
    • Larry Paul HeckMadhusudan ChinthakuntaRukmini Iyer
    • G06F17/30
    • G06F16/20
    • Within the field of computing, many scenarios involve queries formulated by users resulting in query results presented by a device. The user may request to adjust the query, but many devices can only process requests specified in a well-structured manner, such as a set of recognized keywords, specific verbal commands, or a specific manual gesture. The user thus communicates the adjustment request in the constraints of the device, even if the query is specified in a natural language. Presented herein are techniques for enabling users to specify query adjustments with natural action input (e.g., natural-language speech, vocal inflection, and natural manual gestures). The device may be configured to evaluate the natural action input, identify the user's intended query adjustments, generate an adjusted query, and present an adjusted query result, thus enabling the user to interact with the device in a similar manner as communicating with an individual.
    • 在计算领域中,许多场景涉及由用户制定的查询,从而产生由设备呈现的查询结果。 用户可以请求调整查询,但是许多设备只能处理以良好结构化方式指定的请求,例如一组已识别的关键字,特定的语言命令或特定的手动手势。 因此,即使以自然语言指定查询,用户因此在设备的约束中传达调整请求。 这里提供的是使用户能够使用自然动作输入(例如,自然语言语音,声音变形和自然手动手势)来指定查询调整的技术。 该设备可以被配置为评估自然动作输入,识别用户的预期查询调整,生成经调整的查询,并呈现经调整的查询结果,从而使得用户能够以与与个人通信相似的方式与设备进行交互。