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    • 4. 发明申请
    • DETERMINING QUERY INTENT
    • 确定查询内容
    • US20110314012A1
    • 2011-12-22
    • US12816389
    • 2010-06-16
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • G06F17/30
    • G06F17/30979
    • A tree structure has a node associated with each category of a hierarchy of item categories. Child nodes of the tree are associated with sub-categories of the categories associated with parent nodes. Training data including received queries and indicators of a selected item category for each received query is combined with the tree structure by associating each query with the node corresponding to the selected category of the query. When a query is received, a classifier is applied to the nodes to generate a probability that the query is intended to match an item of the category associated with the node. The classifier is applied until the probability is below a threshold. One or more categories associated with the nodes that are closest to the intent of the received query are selected and indicators of items of those categories that match the received query are output.
    • 树结构具有与项目类别的层次结构的每个类别相关联的节点。 树的子节点与与父节点相关联的类别的子类别相关联。 通过将每个查询与对应于所选择的查询类别的节点相关联,将包括接收到的查询和针对每个接收到的查询的所选项目类别的指示符的训练数据与树结构组合。 当接收到查询时,分类器被应用于节点以产生查询旨在匹配与节点相关联的类别的项目的概率。 应用分类器直到概率低于阈值。 选择与接收到的查询的意图最接近的节点相关联的一个或多个类别,并输出与接收到的查询匹配的那些类别的项目的指示符。
    • 7. 发明授权
    • Determining query intent
    • 确定查询意图
    • US08612432B2
    • 2013-12-17
    • US12816389
    • 2010-06-16
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • Krishnaram N. G. KenthapadiPanayiotis TsaparasSreenivas GollapudiRakesh Agrawal
    • G06F7/00G06F17/30G06F15/18
    • G06F17/30979
    • A tree structure has a node associated with each category of a hierarchy of item categories. Child nodes of the tree are associated with sub-categories of the categories associated with parent nodes. Training data including received queries and indicators of a selected item category for each received query is combined with the tree structure by associating each query with the node corresponding to the selected category of the query. When a query is received, a classifier is applied to the nodes to generate a probability that the query is intended to match an item of the category associated with the node. The classifier is applied until the probability is below a threshold. One or more categories associated with the nodes that are closest to the intent of the received query are selected and indicators of items of those categories that match the received query are output.
    • 树结构具有与项目类别的层次结构的每个类别相关联的节点。 树的子节点与与父节点相关联的类别的子类别相关联。 通过将每个查询与对应于所选择的查询类别的节点相关联,将包括接收到的查询和针对每个接收到的查询的所选项目类别的指示符的训练数据与树结构组合。 当接收到查询时,分类器被应用于节点以产生查询旨在匹配与节点相关联的类别的项目的概率。 应用分类器直到概率低于阈值。 选择与接收到的查询的意图最接近的节点相关联的一个或多个类别,并输出与接收到的查询匹配的那些类别的项目的指示符。
    • 8. 发明申请
    • OBJECT CLASSIFICATION USING TAXONOMIES
    • 使用TAXONOMIES的对象分类
    • US20100185577A1
    • 2010-07-22
    • US12414065
    • 2009-03-30
    • Panayiotis TsaparasPanagiotis PapadimitriouAriel D. FuxmanLise C. GetoorRakesh Agrawal
    • Panayiotis TsaparasPanagiotis PapadimitriouAriel D. FuxmanLise C. GetoorRakesh Agrawal
    • G06N5/02
    • G06N99/005
    • As provided herein objects from a source catalog, such as a provider's catalog, can be added to a target catalog, such as an enterprise master catalog, in a scalable manner utilizing catalog taxonomies. A baseline classifier determines probabilities for source objects to target catalog classes. Source objects can be assigned to those classes with probabilities that meet a desired threshold and meet a desired rate. A classification cost for target classes can be determined for respective unassigned source objects, which can comprise determining an assignment cost and separation cost for the source objects for respective desired target classes. The separation and assignment costs can be combined to determine the classification cost, and the unassigned source objects can be assigned to those classes having a desired classification cost.
    • 如本文所提供的,可以使用目录分类法将来自源目录的诸如提供者目录的对象以可扩展的方式添加到目标目录,例如企业主目录。 基准分类器确定源对象到目标目录类的概率。 可以将源对象分配给具有满足期望阈值且满足期望速率的概率的那些类。 可以针对相应的未分配的源对象来确定目标类别的分类成本,其可以包括确定用于各个期望目标类别的源对象的分配成本和分离成本。 分离和分配成本可以组合以确定分类成本,并且未分配的源对象可以被分配给具有期望的分类成本的那些类。
    • 10. 发明申请
    • DETERMINING COMPREHENSIVE SUBSETS OF REVIEWS
    • 确定综合综合评估报告
    • US20130060760A1
    • 2013-03-07
    • US13224350
    • 2011-09-02
    • Panayiotis TsaparasAlexandros NtoulasEvimaria Terzi
    • Panayiotis TsaparasAlexandros NtoulasEvimaria Terzi
    • G06F17/30
    • G06F16/355
    • Techniques are provided for selecting a limited but comprehensive set of high-quality users reviews covering several different aspects or attributes of a reviewed item. For several implementations, selection methodologies approach the challenge as a maximum coverage problem and provide a generic formalism to model the different variants of the review-set selection. Variations to such implementation may also employ different algorithms in consideration of different variants and weightings of those variants. Select implementations employ methodologies that collectively consider attributes of the item discussed in the reviews, the quality of the reviews themselves, and the viewpoint of the reviews (e.g., positive or negative) as input values in order to provide outputs that cover as many attributes of the item as possible, comprising high quality reviews representing different viewpoints.
    • 提供技术用于选择覆盖所审查项目的几个不同方面或属性的有限但全面的高质量用户评论。 对于多个实施方案,选择方法将挑战视为最大覆盖问题,并提供通用的形式主义以对审查集选择的不同变体进行建模。 考虑到这些变型的不同变体和权重,这种实现的变化也可以采用不同的算法。 选择实施采用集体考虑审查中讨论的项目的属性,评论本身的质量以及评论的观点(例如,正或负))作为输入值的方法,以提供涵盖尽可能多的属性的输出 该项目可能包括代表不同观点的高质量评论。