METHOD AND APPARATUS FOR AUTOMATICALLY INCORPORATING HYPOTHETICAL CONTEXT INFORMATION INTO RECOMMENDATION QUERIES
    2.
    发明申请
    METHOD AND APPARATUS FOR AUTOMATICALLY INCORPORATING HYPOTHETICAL CONTEXT INFORMATION INTO RECOMMENDATION QUERIES 有权
    将自动上下文信息纳入建议查询的方法和装置

    公开(公告)号:US20110137927A1

    公开(公告)日:2011-06-09

    申请号:US13028020

    申请日:2011-02-15

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30867 H04W4/029

    摘要: A system facilitates automatically determining the hypothetical context information or the distribution of hypothetical contexts. During operation, the system receives a request from a user for one or more recommendations. The system also receives a current context substantially associated with the request. The system then determines a hypothetical context for the request, wherein the hypothetical context may be determined by considering several sources of information, including but not limited to the current context, past contexts, and relationships between the current context and past contexts. Next, the system determines one or more recommendations for the user based on the hypothetical context. Finally, the system returns the one or more recommendations to the user.

    摘要翻译: 系统有助于自动确定假设上下文信息或假设上下文的分布。 在操作期间,系统从用户接收一个或多个建议的请求。 该系统还接收与该请求基本相关联的当前上下文。 然后,该系统确定该请求的假设上下文,其中假设上下文可以通过考虑若干信息来确定,包括但不限于当前上下文,过去上下文以及当前上下文与过去上下文之间的关系。 接下来,系统基于假设上下文确定用户的一个或多个建议。 最后,系统将一个或多个建议返回给用户。

    Method and apparatus for automatically incorporating hypothetical context information into recommendation queries
    3.
    发明授权
    Method and apparatus for automatically incorporating hypothetical context information into recommendation queries 有权
    将假设上下文信息自动并入推荐查询的方法和装置

    公开(公告)号:US08874605B2

    公开(公告)日:2014-10-28

    申请号:US13028020

    申请日:2011-02-15

    IPC分类号: G06F17/30

    CPC分类号: G06F17/30867 H04W4/029

    摘要: A system facilitates automatically determining the hypothetical context information or the distribution of hypothetical contexts. During operation, the system receives a request from a user for one or more recommendations. The system also receives a current context substantially associated with the request. The system then determines a hypothetical context for the request, wherein the hypothetical context may be determined by considering several sources of information, including but not limited to the current context, past contexts, and relationships between the current context and past contexts. Next, the system determines one or more recommendations for the user based on the hypothetical context. Finally, the system returns the one or more recommendations to the user.

    摘要翻译: 系统有助于自动确定假设上下文信息或假设上下文的分布。 在操作期间,系统从用户接收一个或多个建议的请求。 该系统还接收与该请求基本相关联的当前上下文。 然后,该系统确定该请求的假设上下文,其中假设上下文可以通过考虑若干信息来确定,包括但不限于当前上下文,过去上下文以及当前上下文与过去上下文之间的关系。 接下来,系统基于假设上下文确定用户的一个或多个建议。 最后,系统将一个或多个建议返回给用户。

    MIXED-MODEL RECOMMENDER FOR LEISURE ACTIVITIES
    4.
    发明申请
    MIXED-MODEL RECOMMENDER FOR LEISURE ACTIVITIES 有权
    用于休闲活动的混合模式推荐

    公开(公告)号:US20090077057A1

    公开(公告)日:2009-03-19

    申请号:US11856913

    申请日:2007-09-18

    IPC分类号: G06F17/30

    CPC分类号: G06Q30/02

    摘要: One embodiment of the present invention provides a method for recommending leisure activities to a user. During operation, the system receives at least one query for leisure activities. The system then determines a collaborative filtering score of a candidate activity based on a collaborative filtering model, a soft query score for the candidate activity based on a soft query model, a content preference score for the candidate activity based on a content preference model and the user's past behavior, and a distance score for the candidate activity based on a distance model. Next, the system generates a composite score for the candidate activity by calculating a weighted average of the collaborative filtering score, the soft query score, the content preference score, and the distance score. The system further returns a recommendation list containing the activities with the highest composite scores.

    摘要翻译: 本发明的一个实施例提供了一种向用户推荐休闲活动的方法。 在运营期间,系统至少收到一个休闲活动查询。 然后,系统基于协同过滤模型,基于软查询模型的候选活动的软查询分数,基于内容偏好模型的候选活动的内容偏好分数来确定候选活动的协作过滤分数,以及 用户的过去行为以及基于距离模型的候选活动的距离得分。 接下来,系统通过计算协同过滤分数,软查询分数,内容偏好分数和距离分数的加权平均来生成候选活动的综合分数。 该系统进一步返回包含具有最高综合得分的活动的推荐列表。

    Method and apparatus for automatically incorporating hypothetical context information into recommendation queries
    5.
    发明授权
    Method and apparatus for automatically incorporating hypothetical context information into recommendation queries 有权
    将假设上下文信息自动并入推荐查询的方法和装置

    公开(公告)号:US07904530B2

    公开(公告)日:2011-03-08

    申请号:US12021623

    申请日:2008-01-29

    IPC分类号: G06F15/16

    CPC分类号: G06F17/30867 H04W4/029

    摘要: A system facilitates automatically determining the hypothetical context information or the distribution of hypothetical contexts. During operation, the system receives a request from a user for one or more recommendations. The system also receives a current context substantially associated with the request. The system then determines a hypothetical context for the request, wherein the hypothetical context may be determined by considering several sources of information, including but not limited to the current context, past contexts, and relationships between the current context and past contexts. Next, the system determines one or more recommendations for the user based on the hypothetical context. Finally, the system returns the one or more recommendations to the user.

    摘要翻译: 系统有助于自动确定假设上下文信息或假设上下文的分布。 在操作期间,系统从用户接收一个或多个建议的请求。 该系统还接收与该请求基本相关联的当前上下文。 然后,该系统确定该请求的假设上下文,其中假设上下文可以通过考虑若干信息来确定,包括但不限于当前上下文,过去上下文以及当前上下文与过去上下文之间的关系。 接下来,系统基于假设上下文确定用户的一个或多个建议。 最后,系统将一个或多个建议返回给用户。

    Recommender system with AD-HOC, dynamic model composition
    6.
    发明授权
    Recommender system with AD-HOC, dynamic model composition 有权
    推荐系统采用AD-HOC,动态模型组成

    公开(公告)号:US07836001B2

    公开(公告)日:2010-11-16

    申请号:US11855547

    申请日:2007-09-14

    IPC分类号: G06F17/00 G06N5/00 G06N5/02

    CPC分类号: G06Q30/02

    摘要: One embodiment of the present invention provides recommender system for generating a recommendation of an item by combining a set of utility models adaptively to facilitate a decision-making process. The system includes a utility model database containing the set of utility models and a query module for receiving at least one query about the item from a querying entity. The system also includes a rule engine to specify a subset of utility models to be applied to the item and to specify a weight function of the specified utility models. Further included in the system is a set generator coupled to the utility model database, the query module, and the rule engine. The set generator computes a set of ratings by applying each of the utility model in the subset to the item and generates an overall rating for the item based on the weight function. The system further a communication module to return the overall rating.

    摘要翻译: 本发明的一个实施例提供了一种推荐系统,用于通过自适应地组合一组实用新型来产生项目的推荐,以促进决策过程。 该系统包括实用新型数据库,该实用新型数据库包含一组实用新型,以及用于从查询实体接收关于该项目的至少一个查询的查询模块。 该系统还包括规则引擎,用于指定要应用于项目的实用新型的子集,并指定指定的实用新型的权重函数。 系统中还包括一个耦合到实用新型数据库,查询模块和规则引擎的集合生成器。 集合生成器通过将子集中的每个实用新型应用于项目来计算一组评级,并且基于权重函数生成该项目的总体评级。 该系统还提供一个通信模块来返回整体评级。

    METHOD AND APPARATUS FOR AUTOMATICALLY INCORPORATING HYPOTHETICAL CONTEXT INFORMATION INTO RECOMMENDATION QUERIES
    7.
    发明申请
    METHOD AND APPARATUS FOR AUTOMATICALLY INCORPORATING HYPOTHETICAL CONTEXT INFORMATION INTO RECOMMENDATION QUERIES 有权
    将自动上下文信息纳入建议查询的方法和装置

    公开(公告)号:US20090193099A1

    公开(公告)日:2009-07-30

    申请号:US12021623

    申请日:2008-01-29

    IPC分类号: G06F15/16

    CPC分类号: G06F17/30867 H04W4/029

    摘要: A system facilitates automatically determining the hypothetical context information or the distribution of hypothetical contexts. During operation, the system receives a request from a user for one or more recommendations. The system also receives a current context substantially associated with the request. The system then determines a hypothetical context for the request, wherein the hypothetical context may be determined by considering several sources of information, including but not limited to the current context, past contexts, and relationships between the current context and past contexts. Next, the system determines one or more recommendations for the user based on the hypothetical context. Finally, the system returns the one or more recommendations to the user.

    摘要翻译: 系统有助于自动确定假设上下文信息或假设上下文的分布。 在操作期间,系统从用户接收一个或多个建议的请求。 该系统还接收与该请求基本相关联的当前上下文。 然后,该系统确定该请求的假设上下文,其中假设上下文可以通过考虑若干信息来确定,包括但不限于当前上下文,过去上下文以及当前上下文与过去上下文之间的关系。 接下来,系统基于假设上下文确定用户的一个或多个建议。 最后,系统将一个或多个建议返回给用户。

    RECOMMENDER SYSTEM WITH AD-HOC, DYNAMIC MODEL COMPOSITION
    9.
    发明申请
    RECOMMENDER SYSTEM WITH AD-HOC, DYNAMIC MODEL COMPOSITION 有权
    具有AD-HOC,动态模型组合的推荐系统

    公开(公告)号:US20090076997A1

    公开(公告)日:2009-03-19

    申请号:US11855547

    申请日:2007-09-14

    IPC分类号: G06N5/00 G06N5/02 G06F17/00

    CPC分类号: G06Q30/02

    摘要: One embodiment of the present invention provides recommender system for generating a recommendation of an item by combining a set of utility models adaptively to facilitate a decision-making process. The system includes a utility model database containing the set of utility models and a query module for receiving at least one query about the item from a querying entity. The system also includes a rule engine to specify a subset of utility models to be applied to the item and to specify a weight function of the specified utility models. Further included in the system is a set generator coupled to the utility model database, the query module, and the rule engine. The set generator computes a set of ratings by applying each of the utility model in the subset to the item and generates an overall rating for the item based on the weight function. The system further a communication module to return the overall rating.

    摘要翻译: 本发明的一个实施例提供了一种推荐系统,用于通过自适应地组合一组实用新型来产生项目的推荐,以促进决策过程。 该系统包括实用新型数据库,该实用新型数据库包含一组实用新型,以及用于从查询实体接收关于该项目的至少一个查询的查询模块。 该系统还包括规则引擎,用于指定要应用于项目的实用新型的子集,并指定指定的实用新型的权重函数。 系统中还包括一个耦合到实用新型数据库,查询模块和规则引擎的集合生成器。 集合生成器通过将子集中的每个实用新型应用于项目来计算一组评级,并基于权重函数生成项目的总体评级。 该系统还提供一个通信模块来返回整体评级。

    Performance-efficient system for predicting user activities based on time-related features
    10.
    发明授权
    Performance-efficient system for predicting user activities based on time-related features 有权
    基于时间相关功能预测用户活动的高效系统

    公开(公告)号:US09183497B2

    公开(公告)日:2015-11-10

    申请号:US13403129

    申请日:2012-02-23

    IPC分类号: G06N5/02 G06N7/00 G06Q30/02

    摘要: A recommender system uses an activity decision tree to model the changes in a user's behavior according to a plurality of time-related features. The system determines historical activities for the user, and generates a decision tree for the user's historical activities. Each leaf node of the decision tree is associated with an activity-prediction model that computes a probability for a corresponding activity. The system selects a path of the decision tree from a root node to a leaf node of the decision tree based on a target time. The selected path traverses two or more non-leaf nodes that are each associated with a temporal decision model that compares the target time against a temporal classifier. The system then determines a probability for a user activity based on an activity-prediction model of the selected path.

    摘要翻译: 推荐系统使用活动决策树来根据多个时间相关特征对用户行为的变化进行建模。 系统确定用户的历史活动,并为用户的历史活动生成决策树。 决策树的每个叶节点与计算相应活动概率的活动预测模型相关联。 系统基于目标时间从决策树的根节点到叶节点选择决策树的路径。 所选择的路径遍历两个或多个非叶节点,每个非叶节点与时间决策模型相关联,时间决策模型将目标时间与时间分类器进行比较。 然后,系统基于所选路径的活动预测模型来确定用户活动的概率。