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1. 发明申请

US20120089581A1 Informing Search Results Based on Commercial Transaction Publications 审中-公开
标题翻译：基于商业交易出版物的搜索结果通知
公开(公告)号：US20120089581A1
公开(公告)日：2012-04-12
申请号：US12899569
申请日：2010-10-07
申请人： Anoop Gupta , Thore Graepel , Ralf Herbrich
发明人： Anoop Gupta , Thore Graepel , Ralf Herbrich
IPC分类号： G06F17/30 , G06F15/16
CPC分类号： G06Q10/00 , G06Q30/00
摘要： A publishing engine captures capturing commercial events and other information (collectively, “commercial information”) associated with a first user and automatically notifies other users in the social network of the first user of this commercial information. The publishing engine also notifies one or more search engines of these events and information. Based on this commercial information, the search engine can augment search results of the members of the social network to include historical notifications relating to commercial transactions for similar products and/or services by others in their social network. In this manner, for example, the search engine can provide results directing the searcher to other users in their social network who have purchased such products and/or services.
摘要翻译：发布引擎捕获与第一用户相关联的商业事件和其他信息（统称为“商业信息”），并自动通知该商业信息的第一用户的社交网络中的其他用户。发布引擎还通知一个或多个搜索引擎的这些事件和信息。基于这种商业信息，搜索引擎可以增加社交网络成员的搜索结果，以包括与他们的社交网络中的其他类似产品和/或服务相关的商业交易的历史通知。以这种方式，例如，搜索引擎可以提供将搜索者指向已经购买了这样的产品和/或服务的社交网络中的其他用户的结果。

2. 发明申请

US20120089446A1 Publishing Commercial Information in a Social Network 审中-公开
标题翻译：在社交网络中发布商业信息
公开(公告)号：US20120089446A1
公开(公告)日：2012-04-12
申请号：US12899566
申请日：2010-10-07
申请人： Anoop Gupta , Thore Graepel , Ralf Herbrich
发明人： Anoop Gupta , Thore Graepel , Ralf Herbrich
IPC分类号： G06Q30/00
CPC分类号： G06Q30/0208 , G06Q30/0601 , G06Q50/01
摘要： A publishing engine captures commercial information associated with a first user and automatically notifies other users in the first user's social network of this commercial information. The first user authorizes an e-commerce system to access his or her social network and to publish commercial information about the first user's commercial activity (e.g., a purchase or other commercial transaction) to users in the social network. By this automated notification, the notified users in the first user's social network can learn that the first user has completed a commercial transaction pertaining to a particular product or service. If a notified user is interested in a similar product or service, he or she can contact the first user to inquire about the first user's experience and information with the product or service.
摘要翻译：发布引擎捕获与第一用户相关联的商业信息，并自动通知第一用户的社交网络中的其他用户该商业信息。第一个用户授权电子商务系统访问他或她的社交网络，并且向社交网络中的用户发布关于第一用户的商业活动（例如，购买或其他商业交易）的商业信息。通过该自动通知，第一用户社交网络中通知的用户可以知道第一用户已经完成了与特定产品或服务有关的商业交易。如果通知用户对类似的产品或服务感兴趣，他或她可以联系第一个用户以查询第一个用户的体验和产品或服务的信息。

3. 发明授权

US09413557B2 Pricing in social advertising 有权
标题翻译：社交广告定价
公开(公告)号：US09413557B2
公开(公告)日：2016-08-09
申请号：US12818161
申请日：2010-06-18
申请人： Ralf Herbrich , Thore Graepel , Yoram Bachrach
发明人： Ralf Herbrich , Thore Graepel , Yoram Bachrach
IPC分类号： G06Q30/00 , H04L12/58 , G06Q30/02 , G06Q50/00
CPC分类号： H04L12/5855 , G06Q30/0214 , G06Q30/0273 , G06Q50/01 , H04L51/14 , H04L51/32
摘要： Online recommendations are tracked through a forwarding service. The forwarding service can provide such statistics to an ad service, which can provide incentives to the recommending user and a consuming user. Example incentives may include an accumulation of points by the recommending user, a discount to the consuming user if a purchase is made in response to the recommendation, etc. To determine how much of an incentive each participant in the recommendation flow receives, a graph is created to model the recommendation flow and incentives are allocated using a cooperative game description based on this graph that associates each participant with a power index that represents that participants share of the incentive.
摘要翻译：通过转发服务跟踪在线建议。转发服务可以将这样的统计信息提供给广告服务，其可以向推荐用户和消费用户提供激励。示例性激励可以包括推荐用户的积分积分，如果响应于推荐而进行购买，则对消费用户的折扣等。为了确定推荐流程中每个参与者接收到的激励多少，创建以建模流程的模型和激励是使用基于该图的合作游戏描述来分配的，其将每个参与者与表示激励的参与者份额的权力指数相关联。

4. 发明申请

US20070112706A1 Handicapping in a Bayesian skill scoring framework 审中-公开
标题翻译：在贝叶斯技能评分框架中的障碍
公开(公告)号：US20070112706A1
公开(公告)日：2007-05-17
申请号：US11607482
申请日：2006-11-30
申请人： Ralf Herbrich , Thore Graepel
发明人： Ralf Herbrich , Thore Graepel
IPC分类号： G06F15/18
CPC分类号： G07F17/3274 , G07F17/32
摘要： A skill scoring frameworks allows for handicapping an individual game player in a gaming environment in preparation of matching the game player with other game players, whether for building teams or assigning competitors, or both. By introducing handicapping into the skill scoring framework, a highly skilled player may select one or more game characteristics (e.g., a less than optimal racing vehicle, reduced character capabilities, etc.) and therefore be assigned a handicap that allows the player to be matched with lower skilled players for competitive game play. Handicaps may apply positively or negatively a player's skill score during the matching stage. Handicaps may also be updated based on the game outcomes of the game play in which they were applied.
摘要翻译：技能评分框架允许在游戏环境中妨碍个人游戏玩家，以准备将游戏玩家与其他游戏玩家相匹配，无论是建立团队还是分配竞争对手，或两者兼有。通过在技能评分框架中引入障碍，高技能玩家可以选择一个或多个游戏特征（例如，不太优化的赛车，减少的角色能力等），并且因此被分配允许玩家匹配的障碍与较低技术的玩家竞争游戏。障碍可能在比赛阶段积极或消极地运用玩家的技能得分。还可以根据应用游戏结果的游戏结果更新障碍。

5. 发明授权

US08364612B2 Machine learning using relational databases 有权
标题翻译：机器学习使用关系数据库
公开(公告)号：US08364612B2
公开(公告)日：2013-01-29
申请号：US12559921
申请日：2009-09-15
申请人： Jurgen Anne Francios Marie Van Gael , Ralf Herbrich , Thore Graepel
发明人： Jurgen Anne Francios Marie Van Gael , Ralf Herbrich , Thore Graepel
IPC分类号： G06F15/18
CPC分类号： G06N99/005
摘要： Machine learning using relational databases is described. In an embodiment a model of a probabilistic relational database is formed by augmenting relation schemas of a relational database with probabilistic attributes. In an example, the model comprises constraints introduced by linking the probabilistic attributes using factor statements. For example, a compiler translates the model into a factor graph data structure which may be passed to an inference engine to carry out machine learning. For example, this enables machine learning to be integrated with the data and it is not necessary to pre-process or reformat large scale data sets for a particular problem domain. In an embodiment a machine learning system for estimating skills of players in an online gaming environment is provided. In another example, a machine learning system for data mining of medical data is provided. In some examples, missing attribute values are filled using machine learning results.
摘要翻译：描述使用关系数据库的机器学习。在一个实施例中，通过用概率属性来增加关系数据库的关系模式来形成概率关系数据库的模型。在一个例子中，模型包括通过使用因子语句链接概率属性引入的约束。例如，编译器将该模型转换为因子图数据结构，该结构可被传递给推理机以执行机器学习。例如，这使得机器学习能够与数据集成，并且不需要为特定问题域预处理或重新格式化大规模数据集。在一个实施例中，提供了一种用于估计在线游戏环境中的玩家的技能的机器学习系统。在另一示例中，提供了用于医疗数据的数据挖掘的机器学习系统。在一些示例中，使用机器学习结果填充缺少的属性值。

6. 发明申请

US20110066577A1 Machine Learning Using Relational Databases 有权
标题翻译：机器学习使用关系数据库
公开(公告)号：US20110066577A1
公开(公告)日：2011-03-17
申请号：US12559921
申请日：2009-09-15
申请人： Jurgen Anne Francois Marie Van Gael , Ralf Herbrich , Thore Graepel
发明人： Jurgen Anne Francois Marie Van Gael , Ralf Herbrich , Thore Graepel
IPC分类号： G06F15/18 , G06N5/04 , G06F17/30
CPC分类号： G06N99/005
摘要： Machine learning using relational databases is described. In an embodiment a model of a probabilistic relational database is formed by augmenting relation schemas of a relational database with probabilistic attributes. In an example, the model comprises constraints introduced by linking the probabilistic attributes using factor statements. For example, a compiler translates the model into a factor graph data structure which may be passed to an inference engine to carry out machine learning. For example, this enables machine learning to be integrated with the data and it is not necessary to pre-process or reformat large scale data sets for a particular problem domain. In an embodiment a machine learning system for estimating skills of players in an online gaming environment is provided. In another example, a machine learning system for data mining of medical data is provided. In some examples, missing attribute values are filled using machine learning results.
摘要翻译：描述使用关系数据库的机器学习。在一个实施例中，通过用概率属性来增加关系数据库的关系模式来形成概率关系数据库的模型。在一个例子中，模型包括通过使用因子语句链接概率属性引入的约束。例如，编译器将该模型转换为因子图数据结构，该结构可被传递给推理机以执行机器学习。例如，这使得机器学习能够与数据集成，并且不需要为特定问题域预处理或重新格式化大规模数据集。在一个实施例中，提供了一种用于估计在线游戏环境中的玩家的技能的机器学习系统。在另一示例中，提供了用于医疗数据的数据挖掘的机器学习系统。在一些示例中，使用机器学习结果填充缺少的属性值。

7. 发明申请

US20100262568A1 Scalable Clustering 有权
标题翻译：可扩展聚类
公开(公告)号：US20100262568A1
公开(公告)日：2010-10-14
申请号：US12421853
申请日：2009-04-10
申请人： Anton Schwaighofer , Joaquin Quinonero Candela , Thomas Borchert , Thore Graepel , Ralf Herbrich
发明人： Anton Schwaighofer , Joaquin Quinonero Candela , Thomas Borchert , Thore Graepel , Ralf Herbrich
IPC分类号： G06N5/02 , G06F15/18
CPC分类号： G06N99/005 , G06K9/6226
摘要： A scalable clustering system is described. In an embodiment the clustering system is operable for extremely large scale applications where millions of items having tens of millions of features are clustered. In an embodiment the clustering system uses a probabilistic cluster model which models uncertainty in the data set where the data set may be for example, advertisements which are subscribed to keywords, text documents containing text keywords, images having associated features or other items. In an embodiment the clustering system is used to generate additional features for associating with a given item. For example, additional keywords are suggested which an advertiser may like to subscribe to. The additional features that are generated have associated probability values which may be used to rank those features in some embodiments. User feedback about the generated features is received and used to revise the feature generation process in some examples.
摘要翻译：描述了可扩展的集群系统。在一个实施例中，聚类系统可操作用于具有数千万个特征的数百万个项目被聚集的极大规模应用。在一个实施例中，聚类系统使用概率聚类模型，其对数据集中的不确定性进行建模，其中数据集可以是例如订阅关键字的广告，包含文本关键字的文本文档，具有相关联特征或其他项目的图像。在一个实施例中，聚类系统用于产生用于与给定项目相关联的附加特征。例如，建议广告客户可能希望订阅的其他关键字。生成的附加特征具有相关联的概率值，其可用于在某些实施例中对这些特征进行排名。在一些示例中，接收并用于用户对生成的特征的反馈以修改特征生成过程。

8. 发明申请

US20070265718A1 TEAM MATCHING 失效
标题翻译：团队匹配
公开(公告)号：US20070265718A1
公开(公告)日：2007-11-15
申请号：US11561374
申请日：2006-11-17
申请人： Thore Graepel , Ralf Herbrich
发明人： Thore Graepel , Ralf Herbrich
IPC分类号： G06F19/00
CPC分类号： G07F17/32 , G07F17/3276
摘要： Players in a gaming environment, particularly, electronic on-line gaming environments, may be scored relative to each other or to a predetermined scoring system. The scoring of each player may be based on the outcomes of games between players who compete against each other in one or more teams of one or more players. Each player's score may be represented as a distribution over potential scores which may indicate a confidence level in the distribution representing the player's score. The score distribution for each player may be modeled with a Gaussian distribution and may be determined through a Bayesian inference algorithm. The scoring may be used to track a player's progress and/or standing within the gaming environment, used in a leaderboard indication of rank, and/or may be used to match players with each other in a future game. The matching of one or more teams in a potential game may be evaluated using a match quality threshold which indicates a measure of expected match quality that can be related to the probability distribution over game outcomes.
摘要翻译：在游戏环境中，特别是电子在线游戏环境中的玩家可以相对于彼此或预定的评分系统进行打分。每个玩家的得分可以基于在一个或多个玩家的一个或多个队中彼此竞争的玩家之间的游戏的结果。每个玩家的得分可以表示为潜在分数的分布，其可以指示表示玩家得分的分布中的置信水平。每个玩家的得分分布可以用高斯分布来建模，并且可以通过贝叶斯推理算法来确定。评分可以用于跟踪玩家在排行榜中使用的游戏环境中的进展和/或站立，并且/或可以用于在未来的游戏中将玩家彼此匹配。可以使用匹配质量阈值来评估潜在游戏中的一个或多个团队的匹配，该匹配质量阈值指示可以与游戏结果的概率分布相关的预期匹配质量的度量。

9. 发明申请

US20070110298A1 Stereo video for gaming 有权
标题翻译：用于游戏的立体声视频
公开(公告)号：US20070110298A1
公开(公告)日：2007-05-17
申请号：US11272950
申请日：2005-11-14
申请人： Thore Graepel , Andrew Blake , Ralf Herbrich
发明人： Thore Graepel , Andrew Blake , Ralf Herbrich
IPC分类号： G06K9/00 , G09G5/00
CPC分类号： H04N13/239 , A63F13/213 , A63F2300/1093 , G06K9/00355 , G06T7/593 , G06T15/00 , G06T2207/10012 , H04N13/207
摘要： A real-time stereo video signal of a captured scene with a physical foreground object and a physical background is received. In real-time, a foreground/background separation algorithm is used on the real-time stereo video signal to identify pixels from the stereo video signal that represent the physical foreground object. A video sequence is produced by rendering a 3d virtual reality based on the identified pixels of the physical foreground object.
摘要翻译：接收具有物理前景对象和物理背景的捕获场景的实时立体视频信号。实时地，在实时立体视频信号上使用前景/背景分离算法来识别来自表示物理前景对象的立体视频信号的像素。通过基于所识别的物理前景对象的像素渲染3d虚拟现实来产生视频序列。

10. 发明授权

US08781915B2 Recommending items to users utilizing a bi-linear collaborative filtering model 有权
标题翻译：使用双线性协同过滤模型向用户推荐项目
公开(公告)号：US08781915B2
公开(公告)日：2014-07-15
申请号：US12253854
申请日：2008-10-17
申请人： Ralf Herbrich , Thore Graepel , David Stern
发明人： Ralf Herbrich , Thore Graepel , David Stern
IPC分类号： G06Q10/00
CPC分类号： G06Q30/0633 , G06Q30/02 , G06Q30/0203
摘要： A recommender system may be used to predict a user behavior that a user will give in relation to an item. In an embodiment such predictions are used to enable items to be recommended to users. For example, products may be recommended to customers, potential friends may be recommended to users of a social networking tool, organizations may be recommended to automated users or other items may be recommended to users. In an embodiment a memory stores a data structure specifying a bi-linear collaborative filtering model of user behaviors. In the embodiment an automated inference process may be applied to the data structure in order to predict a user behavior given information about a user and information about an item. For example, the user information comprises user features as well as a unique user identifier.
摘要翻译：推荐系统可以用于预测用户将相对于项目给出的用户行为。在一个实施例中，这样的预测用于使得可以向用户推荐项目。例如，产品可能会推荐给客户，潜在的朋友可能会推荐给社交网络工具的用户，组织可能会推荐给自动化用户或其他项目可能推荐给用户。在一个实施例中，存储器存储指定用户行为的双线性协同过滤模型的数据结构。在该实施例中，自动推理过程可以应用于数据结构，以便预测给定关于用户的信息的用户行为和关于项目的信息。例如，用户信息包括用户特征以及唯一的用户标识符。

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