专利快速检索-快速检索全球专利，免费商用专利数据库-IPRDB

1. 发明授权

US08086555B2 Collaborative filtering systems and methods 有权
标题翻译：协同过滤系统和方法
公开(公告)号：US08086555B2
公开(公告)日：2011-12-27
申请号：US12359167
申请日：2009-01-23
申请人： Rong Pan , Rajan Lukose , Martin B. Scholz
发明人： Rong Pan , Rajan Lukose , Martin B. Scholz
IPC分类号： G06F9/44 , G06N7/02 , G06N7/06
CPC分类号： G06F17/30029 , G06F17/30867 , G06Q10/04
摘要： A collaborative filtering method for evaluating a group of items to aid in predicting utility of items for a particular user comprises assigning an item value of either known or missing to each item of the group of items, and applying a modification scheme to the item values of the missing items to assign a confidence value to each of the item values of the missing items to thereby generate a group of modified item values. The group of items having modified item values and the group known items are evaluated to generate a prediction of utility of items for a particular user.
摘要翻译：用于评估一组项目以帮助预测特定用户的项目的效用的协同过滤方法包括将已知或缺失的项目值分配给该组项目的每个项目，并将修改方案应用于项目值丢失的项目来为缺失项目的每个项目值分配置信度值，从而生成一组修改后的项目值。对具有修改项目值的项目组和组已知项目进行评估以产生用于特定用户的项目的效用的预测。

2. 发明申请

US20100274808A1 SYSTEM AND METHOD FOR MAKING A RECOMMENDATION BASED ON USER DATA 有权
标题翻译：基于用户数据建立建议的系统和方法
公开(公告)号：US20100274808A1
公开(公告)日：2010-10-28
申请号：US12430411
申请日：2009-04-27
申请人： Martin B. Scholz , Rong Pan , Rajan Lukose
发明人： Martin B. Scholz , Rong Pan , Rajan Lukose
IPC分类号： G06F17/30
CPC分类号： G06Q30/0631 , G06F17/30345 , G06F17/30861 , G06F17/30867 , H04L67/025 , H04L67/22
摘要： There is described a system and computer-implemented method for providing a recommendation based on a sparse pattern of data. An exemplary method comprises determining a likelihood that an item for which no user preference data is available will be preferred. The exemplary method also comprises determining a likelihood that an item for which user preference data is available for users other than a particular user will be preferred based on the likelihood that the item for which no user preference data is available will be preferred. The exemplary method additionally comprises predicting that an item for which no user preference data relative to the particular user is available will be preferred if the likelihood that the particular user will prefer the item exceeds a certain level.
摘要翻译：描述了一种用于基于稀疏数据模式提供推荐的系统和计算机实现的方法。一种示例性方法包括确定优选不具有用户偏好数据可用的项目的可能性。该示例性方法还包括基于不优选没有用户偏好数据的项目的可能性来确定用户偏好数据可用于除特定用户之外的用户可能优选的可能性。该示例性方法还包括如果特定用户更喜欢该项目的可能性超过一定水平，则预测相对于该特定用户没有用户偏好数据可用的项目将是优选的。

3. 发明授权

US09633117B2 System and method for making a recommendation based on user data 有权
公开(公告)号：US09633117B2
公开(公告)日：2017-04-25
申请号：US12430411
申请日：2009-04-27
申请人： Martin B. Scholz , Rong Pan , Rajan Lukose
发明人： Martin B. Scholz , Rong Pan , Rajan Lukose
IPC分类号： G06F17/30 , G06Q30/06
CPC分类号： G06Q30/0631 , G06F17/30345 , G06F17/30861 , G06F17/30867 , H04L67/025 , H04L67/22
摘要： There is described a system and computer-implemented method for providing a recommendation based on a sparse pattern of data. An exemplary method comprises determining a likelihood that an item for which no user preference data is available will be preferred. The exemplary method also comprises determining a likelihood that an item for which user preference data is available for users other than a particular user will be preferred based on the likelihood that the item for which no user preference data is available will be preferred. The exemplary method additionally comprises predicting that an item for which no user preference data relative to the particular user is available will be preferred if the likelihood that the particular user will prefer the item exceeds a certain level.

4. 发明申请

US20100191694A1 Collaborative Filtering Systems and Methods 有权
标题翻译：协同过滤系统和方法
公开(公告)号：US20100191694A1
公开(公告)日：2010-07-29
申请号：US12359167
申请日：2009-01-23
申请人： Rong Pan , Rajan Lukose , Martin B. Scholz
发明人： Rong Pan , Rajan Lukose , Martin B. Scholz
IPC分类号： G06N5/02 , G06F17/30
CPC分类号： G06F17/30029 , G06F17/30867 , G06Q10/04
摘要： A collaborative filtering method for evaluating a group of items to aid in predicting utility of items for a particular user comprises assigning an item value of either known or missing to each item of the group of items, and applying a modification scheme to the item values of the missing items to assign a confidence value to each of the item values of the missing items to thereby generate a group of modified item values. The group of items having modified item values and the group known items are evaluated to generate a prediction of utility of items for a particular user.
摘要翻译：用于评估一组项目以帮助预测特定用户的项目的效用的协同过滤方法包括将已知或缺失的项目值分配给该组项目的每个项目，并将修改方案应用于项目值丢失的项目来为缺失项目的每个项目值分配置信度值，从而生成一组修改后的项目值。对具有修改项目值的项目组和组已知项目进行评估以产生用于特定用户的项目的效用的预测。

5. 发明申请

US20100325126A1 RECOMMENDATION BASED ON LOW-RANK APPROXIMATION 审中-公开
标题翻译：基于低排名近似推荐
公开(公告)号：US20100325126A1
公开(公告)日：2010-12-23
申请号：US12487254
申请日：2009-06-18
申请人： Shyam S. RAJARAM , Martin B. Scholz , Rong Pan , Rajan Lukose
发明人： Shyam S. RAJARAM , Martin B. Scholz , Rong Pan , Rajan Lukose
IPC分类号： G06F17/30
CPC分类号： G06Q30/02 , G06F16/24578
摘要： A system and method for providing personalized recommendations are disclosed herein. A system includes a processor and a software system executed by the processor. The software system provides a recommendation for an item. The recommendation is based on a comparison of a low-rank approximation of a domain matrix to a user profile. The user profile is based, in part, on the low-rank approximation of the domain matrix.
摘要翻译：本文公开了一种用于提供个性化建议的系统和方法。系统包括由处理器执行的处理器和软件系统。软件系统提供了一个项目的建议。该建议基于对域矩阵的低阶近似与用户简档的比较。用户简档部分地基于域矩阵的低等级近似。

6. 发明申请

US20110106817A1 METHODS AND SYSTEMS FOR DETERMINING UNKNOWNS IN COLLABORATIVE FILTERING 有权
标题翻译：用于确定协同过滤中的知识的方法和系统
公开(公告)号：US20110106817A1
公开(公告)日：2011-05-05
申请号：US12609327
申请日：2009-10-30
申请人： Rong Pan , Martin B. Scholz
发明人： Rong Pan , Martin B. Scholz
IPC分类号： G06F17/30 , G06N7/02
CPC分类号： G06Q30/02 , G06Q30/0282
摘要： Embodiments of the present invention are directed to methods and systems for determining unknowns in rating matrices. In one embodiment, a method comprises forming a rating matrix, where each matrix element corresponds to a known favorable user rating associated with an item or an unknown user rating associated with an item. The method includes determining a weight matrix configured to assign a weight value to each of the unknown matrix elements, and sampling the rating matrix to generate an ensemble of training matrices. Weighted maximum-margin matrix factorization is applied to each training matrix to obtain corresponding sub-rating matrix, the weights based on the weight matrix. The sub-rating matrices are combined to obtain an approximate rating matrix that can be used to recommend items to users based on the rank ordering of the corresponding matrix elements.
摘要翻译：本发明的实施例涉及用于确定评级矩阵中的未知数的方法和系统。在一个实施例中，一种方法包括形成评级矩阵，其中每个矩阵元素对应于与项目相关联的已知有利用户评级或与项目相关联的未知用户评级。该方法包括确定权重矩阵，其被配置为向每个未知矩阵元素分配权重值，以及对该等级矩阵进行采样以生成训练矩阵的集合。加权最大边缘矩阵因子分解被应用于每个训练矩阵以获得相应的次级矩阵，权重基于权重矩阵。将子评级矩阵组合以获得可以用于基于相应矩阵元素的秩排序向用户推荐项目的近似等级矩阵。

7. 发明授权

US08185535B2 Methods and systems for determining unknowns in collaborative filtering 有权
标题翻译：用于确定协同过滤中未知数的方法和系统
公开(公告)号：US08185535B2
公开(公告)日：2012-05-22
申请号：US12609327
申请日：2009-10-30
申请人： Rong Pan , Martin B. Scholz
发明人： Rong Pan , Martin B. Scholz
IPC分类号： G06F7/00 , G06F17/30
CPC分类号： G06Q30/02 , G06Q30/0282
摘要： Embodiments of the present invention are directed to methods and systems for determining unknowns in rating matrices. In one embodiment, a method comprises forming a rating matrix, where each matrix element corresponds to a known favorable user rating associated with an item or an unknown user rating associated with an item. The method includes determining a weight matrix configured to assign a weight value to each of the unknown matrix elements, and sampling the rating matrix to generate an ensemble of training matrices. Weighted maximum-margin matrix factorization is applied to each training matrix to obtain corresponding sub-rating matrix, the weights based on the weight matrix. The sub-rating matrices are combined to obtain an approximate rating matrix that can be used to recommend items to users based on the rank ordering of the corresponding matrix elements.
摘要翻译：本发明的实施例涉及用于确定评级矩阵中的未知数的方法和系统。在一个实施例中，一种方法包括形成评级矩阵，其中每个矩阵元素对应于与项目相关联的已知有利用户评级或与项目相关联的未知用户评级。该方法包括确定权重矩阵，其被配置为向每个未知矩阵元素分配权重值，以及对该等级矩阵进行采样以生成训练矩阵的集合。加权最大边缘矩阵因子分解被应用于每个训练矩阵以获得相应的次级矩阵，权重基于权重矩阵。将子评级矩阵组合以获得可以用于基于相应矩阵元素的秩排序向用户推荐项目的近似等级矩阵。

8. 发明授权

US09355414B2 Collaborative filtering model having improved predictive performance 有权
标题翻译：具有改进的预测性能的协同过滤模型
公开(公告)号：US09355414B2
公开(公告)日：2016-05-31
申请号：US12790844
申请日：2010-05-30
申请人： Martin B. Scholz , George Forman , Rong Pan
发明人： Martin B. Scholz , George Forman , Rong Pan
IPC分类号： G06F7/00 , G07F17/30 , G06Q30/02
CPC分类号： G06Q30/0282 , G06Q30/02
摘要： For each first entity of a subset of a number of first entities, an expected improvement of a predictive performance of a collaborative filtering model if additional ratings of the first entity in relation to a plurality of second entities were obtained is estimated. Particular first entities from the subset of the first entities of which to obtain the additional ratings in relation to the second entities are selected based at least on the expected improvements that have been determined. The additional ratings of the particular first entities in relation to the second entities are obtained.
摘要翻译：对于多个第一实体的子集的每个第一实体，如果获得关于多个第二实体的第一实体的附加额定值，则估计协同过滤模型的预测性能的预期改进。至少根据已经确定的预期改进来选择其第一实体的子集的第二实体，以获得与第二实体相关的附加等级。获得与第二实体相关的特定第一实体的附加额定值。

9. 发明申请

US20110295762A1 Predictive performance of collaborative filtering model 有权
标题翻译：协同过滤模型的预测性能
公开(公告)号：US20110295762A1
公开(公告)日：2011-12-01
申请号：US12790844
申请日：2010-05-30
申请人： Martin B. Scholz , George Forman , Rong Pan
发明人： Martin B. Scholz , George Forman , Rong Pan
IPC分类号： G06Q10/00 , G06F15/18 , G06N5/02 , G06Q30/00
CPC分类号： G06Q30/0282 , G06Q30/02
摘要： For each first entity of a subset of a number of first entities, an expected improvement of a predictive performance of a collaborative filtering model if additional ratings of the first entity in relation to a plurality of second entities were obtained is estimated. Particular first entities from the subset of the first entities of which to obtain the additional ratings in relation to the second entities are selected based at least on the expected improvements that have been determined. The additional ratings of the particular first entities in relation to the second entities are obtained.
摘要翻译：对于多个第一实体的子集的每个第一实体，如果获得关于多个第二实体的第一实体的附加额定值，则估计协同过滤模型的预测性能的预期改进。至少根据已经确定的预期改进来选择其第一实体的子集的第二实体，以获得与第二实体相关的附加等级。获得与第二实体相关的特定第一实体的附加额定值。

10. 发明申请

US20140215085A1 SYSTEM AND METHOD FOR ROBUST ADAPTATION IN ADAPTIVE STREAMING 审中-公开
标题翻译：用于适应性流动中的鲁棒适应的系统和方法
公开(公告)号：US20140215085A1
公开(公告)日：2014-07-31
申请号：US13750223
申请日：2013-01-25
申请人： Zhi Li , Xiaoqing Zhu , Rong Pan , Joshua B. Gahm , Ali C. Begen , David R. Oran
发明人： Zhi Li , Xiaoqing Zhu , Rong Pan , Joshua B. Gahm , Ali C. Begen , David R. Oran
IPC分类号： H04L29/06
CPC分类号： H04L65/4084 , H04L65/4092 , H04L65/80 , H04L67/02
摘要： A method is provided in one example embodiment and includes receiving media data at an adaptive streaming client; updating an estimated available bandwidth associated with a media stream associated with the media data; filtering the estimated available bandwidth; mapping the filtered estimated available bandwidth to a media bitrate for the media stream; and updating a target segment delay that is to control time intervals between consecutive segment downloads of the media stream.
摘要翻译：在一个示例实施例中提供了一种方法，并且包括在自适应流客户端处接收媒体数据; 更新与与所述媒体数据相关联的媒体流相关联的估计可用带宽; 过滤估计的可用带宽; 将所过滤的估计可用带宽映射到媒体流的媒体比特率; 以及更新用于控制媒体流的连续段下载之间的时间间隔的目标段延迟。

你已经成功收藏专利！

检索式保存成功!

IPRDB

热门服务

关于我们

友情链接

联系方式