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11. 发明申请

WO2021133511A1 SEARCHING USING CHANGED FEATURE OF VIEWED ITEM 审中-公开
公开(公告)号：WO2021133511A1
公开(公告)日：2021-07-01
申请号：PCT/US2020/062448
申请日：2020-11-26
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： BARKAN, Oren , RAZIN, Noam , HIRSCH, Roy , KOENIGSTEIN, Noam , NICE, Nir
IPC分类号： G06F16/33 , G06F16/583 , G06F16/3347 , G06F16/9536
摘要： Computerized searching for an item based on a prior viewed item. A displayed item is identified as a query input item to be used in searching for a target item. That input item has an associated set of embedding vectors each representing a respective feature of the input item. Target features of the search are then identified based on the input item. For each feature in the target item that is desired to be the same as the input item, an embedding vector for the input item is accessed as the vector for that feature in the search. For each feature in the target item that is desired to be different than the input item, a special vector associated with that desired value and feature is accessed for that feature in the search. These accessed vectors are then compared against target items to find close matches.

12. 发明申请

WO2021066938A1 MULTI-PHASE DISTRIBUTED TASK COORDINATION 审中-公开
公开(公告)号：WO2021066938A1
公开(公告)日：2021-04-08
申请号：PCT/US2020/045305
申请日：2020-08-07
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： FELDMAN, Michael , SIMHON, Nimrod Ben , KROSKIN, Ayelet , NICE, Nir
IPC分类号： G06F9/52
摘要： The disclosed distributed task coordination ensures task execution while minimizing both the risk of duplicate execution and resources consumed for coordination. Execution is guaranteed, while only best efforts are used to avoid duplication. Example solutions include requesting, by a node, a first lease from a first set of nodes; based at least on obtaining at least one first lease, requesting, by the node, a second lease from a second set of nodes; based at least on the node obtaining at least one second lease, determining a majority holder of second leases; and based at least on obtaining the majority of second leases, executing, by the node, a task associated with the at least one second lease. In some examples, the nodes comprise online processing units (NPUs). In some examples, if a first node begins executing the task and fails, another node automatically takes over to ensure completion.

13. 发明申请

WO2016077255A1 HYBRID EXPLANATIONS IN COLLABORATIVE FILTER BASED RECOMMENDATION SYSTEM 审中-公开
标题翻译：基于协同滤波器的建议系统的混合解释
公开(公告)号：WO2016077255A1
公开(公告)日：2016-05-19
申请号：PCT/US2015/059800
申请日：2015-11-10
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： NICE, Nir , KOENIGSTEIN, Noam , BEN-ELAZAR, Shay
IPC分类号： G06Q30/02 , G06Q30/06
CPC分类号： G06F17/30867 , G06F17/3053 , G06Q30/0255 , G06Q30/0631
摘要： Example apparatus and methods produce an explanation of why a recommendation is being made by an automated collaborative filtering recommendation system. The explanation may include feature categories and features that describe the item being recommended. The feature categories selected and features selected may depend on a personalization level for an item associated with the recommendation, a quality level of the descriptiveness of a feature for the recommendation, and correlations between items and features analyzed by the recommendation system. The feature categories and features may be selected based on an aggregate score that considers and combines the personalization level, the quality level, and the correlations. The quality level may be human curated or may vary directly with the ability of a feature to partition a feature space. Correlations between items and features reflect the degree to which the features are exhibited by the items.
摘要翻译：示例性的设备和方法说明了为什么通过自动化协同过滤推荐系统进行推荐的原因。说明可能包括描述正在推荐的项目的要素类别和特征。所选择的特征类别和所选择的特征可以取决于与推荐相关联的项目的个性化级别，用于推荐的特征的描述性的质量水平以及由推荐系统分析的项目和特征之间的相关性。可以基于考虑并组合个性化水平，质量水平和相关性的综合评分来选择要素类别和特征。质量水平可能是人性化的，或者可以随特征分配特征空间的能力而直接变化。项目和功能之间的相关性反映了项目展示功能的程度。

14. 发明申请

WO2023075935A1 REPRESENTATION LEARNING WITH SIDE INFORMATION 审中-公开
公开(公告)号：WO2023075935A1
公开(公告)日：2023-05-04
申请号：PCT/US2022/042820
申请日：2022-09-08
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC.
发明人： BARKAN, Oren , CACIULARU, Avi , REJWAN, Idan , WEILL, Yonathan , KOENIGSTEIN, Noam , KATZ, Ori , MALKIEL, Itzik , NICE, Nir
IPC分类号： G06F16/35 , G06N20/00
摘要： A relational similarity determination engine receives as input a dataset including a set of entities and co-occurrence data that defines co-occurrence relations for pairs of the entities. The relational similarity determination engine also receives as input side information defining explicit relations between the entities. The relational similarity determination engine jointly models the co-occurrence relations and the explicit relations for the entities to compute a similarity metric for each different pair of entities within the dataset. Based on the computed similarity metrics, the relational similarity determination engine identifies a most similar replacement entity from the dataset for each of the entities within the dataset. For a select entity received as an input, the relational similarity determination engine outputs the identified most similar replacement entity.

15. 发明申请

WO2022271304A1 SELF-SUPERVISED DOCUMENT-TO-DOCUMENT SIMILARITY SYSTEM 审中-公开
公开(公告)号：WO2022271304A1
公开(公告)日：2022-12-29
申请号：PCT/US2022/029096
申请日：2022-05-13
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： MALKIEL, Itzik , GINZBURG, Dvir , KOENIGSTEIN, Noam , BARKAN, Oren , NICE, Nir
IPC分类号： G06F16/335 , G06F16/338 , G06F16/93 , G06F16/337 , G06F18/2113 , G06F18/2178 , G06V10/751 , G06V30/418
摘要： Examples provide a self-supervised language model for document-to-document similarity scoring and ranking long documents of arbitrary length in an absence of similarity labels. In a first stage of a two-staged hierarchical scoring, a sentence similarity matrix is created for each paragraph in the candidate document. A sentence similarity score is calculated based on the sentence similarity matrix. In the second stage, a paragraph similarity matrix is constructed based on aggregated sentence similarity scores associated with the first candidate document. A total similarity score for the document is calculated based on the normalize the paragraph similarity matrix for each candidate document in a collection of documents. The model is trained using a masked language model and intra-and-inter document sampling. The documents are ranked based on the similarity scores for the documents.

16. 发明申请

WO2017209981A1 HIERARCHICAL MULTISOURCE PLAYLIST GENERATION 审中-公开
标题翻译：分层多方播放列表生成
公开(公告)号：WO2017209981A1
公开(公告)日：2017-12-07
申请号：PCT/US2017/033442
申请日：2017-05-19
申请人： MICROSOFT TECHNOLOGY LICENSING, LLC
发明人： KOENIGSTEIN, Noam , NICE, Nir , ELAZAR, Shay Ben , BEREZIN, Yehiel , BARKAN, Oren , ZACCAI, Tal , SHLEVICH, Shimon , SIMHON, Nimrod Ben , NOGUES, Paul , LAVEE, Gal
IPC分类号： G06F17/30
CPC分类号： G06F16/639 , G06F16/4387 , G06F16/68
摘要： A playlist generator that utilizes multiple data sources to rank each track within a set of candidate tracks to enable selection of candidate tracks according to the ranking. Candidate tracks are each scored according to one or more features, such as acoustic similarity and/or similar usage patterns of the candidate track or artist of the candidate track to a current or previously played track or artist. Each feature is weighted according to historical listening patterns surrounding a user-selected playlist seed artist. The weighting may also be further corrected according to historical listening patterns of the particular user. When historical usage data related to a particular seed artist is limited, more generalized historical usage data related to a higher level in a genre hierarchy may be used.
摘要翻译：播放列表生成器利用多个数据源对一组候选音轨内的每个音轨进行排名，以使得能够根据排名选择候选音轨。候选曲目每个根据一个或多个特征来评分，诸如候选曲目或艺术家对当前或先前播放的曲目或艺术家的候选曲目或艺术家的声学相似性和/或类似使用模式。根据用户选择的播放列表种子艺术家周围的历史收听模式对每个功能进行加权。加权也可以根据特定用户的历史收听模式进一步校正。当与特定种子艺术家相关的历史使用数据是有限的时，可以使用与类型层级中的较高级别相关的更一般化的历史使用数据。

17. 发明授权

EP2321928B1 AUTHENTICATION IN A NETWORK USING CLIENT HEALTH ENFORCEMENT FRAMEWORK 有权
公开(公告)号：EP2321928B1
公开(公告)日：2019-05-15
申请号：EP09829541.3
申请日：2009-10-16
申请人： Microsoft Technology Licensing, LLC
发明人： NICE, Nir , EYAL, Anat , NUKALA, Chandrasekhar , ADDAGATLA, Sreenivas , NEYSTADT, Eugene
IPC分类号： G06F21/30

18. 发明授权

EP2347542B1 COMBINING A MOBILE DEVICE AND COMPUTER TO CREATE A SECURE PERSONALIZED ENVIRONMENT 有权
公开(公告)号：EP2347542B1
公开(公告)日：2018-10-17
申请号：EP09826556.4
申请日：2009-10-30
申请人： Microsoft Technology Licensing, LLC
发明人： NICE, Nir , FITOUSSI, Hen
IPC分类号： H04L29/06 , G06F21/00
CPC分类号： H04L63/102 , G06F21/53 , G06F21/57 , G06F2221/2149 , G06F2221/2153 , H04L63/1433
摘要： A mobile device, such as a mobile phone, smart phone, personal music player, handheld game device, and the like, when operatively combined with a PC, creates a secure and personalized computing platform through configuration of the mobile device's CPU (central processing unit) and OS (operating system) to function as an immutable trusted core. The trusted core in the mobile device verifies the integrity of the PC including, for example, that its drivers, applications, and other software are trusted and unmodified, and thus safe to use without presenting a threat to the integrity of the combined computing platform. The mobile device can further optionally store and transport the user's personalization data-including, for example, the user's desktop, applications, data, certificates, settings, and preferences-which can be accessed by the PC when the devices are combined to thus create a personalized computing environment.

19. 发明授权

EP2404258B1 ACCESS CONTROL USING IDENTIFIERS IN LINKS 有权
标题翻译：访问控制使用链接中的标识符
公开(公告)号：EP2404258B1
公开(公告)日：2016-11-23
申请号：EP10749132.6
申请日：2010-02-26
申请人： Microsoft Technology Licensing, LLC
发明人： NEYSTADT, John , NICE, Nir
IPC分类号： G06F21/62
CPC分类号： G06F21/10 , G06F21/6209 , G06F2221/2101 , G06F2221/2137 , G06F2221/2151 , G06Q20/341 , G07F7/1008 , H04L9/3213 , H04L9/3271 , H04L9/3297 , H04L63/0428 , H04L63/083 , H04L2209/603

20. 发明公开

EP2936339A2 FEATURE EMBEDDING IN MATRIX FACTORIZATION 审中-公开
标题翻译：特点在嵌入式矩阵分解
公开(公告)号：EP2936339A2
公开(公告)日：2015-10-28
申请号：EP13829056.4
申请日：2013-12-19
申请人： Microsoft Technology Licensing, LLC
发明人： NICE, Nir , KOENIGSTEIN, Noam , PAQUET, Ulrich , KEREN, Shahar Zvi , JAFFRAY, Andrew
IPC分类号： G06F17/16 , G06Q30/00 , G06F17/30
CPC分类号： G06F17/16
摘要： In various embodiments, systems and methods are provided for enhancing media content recommendations by using feature vectors. An enhanced-matrix having a first portion and a second portion is received. The first portion of the enhanced-matrix includes a user-item matrix and the second portion of the enhanced-matrix includes a feature-item matrix. Each entry in the feature-item matrix is item metadata. An item-stem vector is determined based on a weighted sum of each of the feature vectors associated with the item. An item-latent-trait vector is generated based on the item-stem vector and an item-offset vector. The item-offset vector is an item vector for the item in the user-item matrix. One or more recommended-media content derived based on the item-latent-trait vector is provided.

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