公开(公告)号：US20210406838A1

公开(公告)日：2021-12-30

申请号：US16912245

申请日：2020-06-25

Applicant: Microsoft Technology Licensing, LLC

Inventor： Rohan Ramanath ,  Konstantin Salomatin ,  Jeffrey Douglas Gee ,  Onkar Anant Dalal ,  Gungor Polatkan ,  Sara Smoot Gerrard ,  Deepak Kumar ,  Rupesh Gupta ,  Jiaqi Ge ,  Lingjie Weng ,  Shipeng Yu

IPC: G06Q10/10 ,  G06N5/04 ,  G06K9/62 ,  G06F16/958 ,  G06F16/9535 ,  G06Q50/00

Abstract: In some embodiments, a computer system generates a recommendation for a user of an online service based on user actions that have been performed by the user within a threshold amount of time before the generation of the recommendation. For each user action, the computer system determines an intent classification that identifies an activity of the user and that corresponds to different types of user actions, as well as a preference classification that identifies a target of the activity, and then stores these intent and preference classifications as part of indications of the user actions for use in generating different types of recommendations using different types of recommendation models. Additionally, the computer system may use mini-batches of data from an incoming stream of logged data to train an incremental update to one or more recommendation models.

公开(公告)号：US11048876B2

公开(公告)日：2021-06-29

申请号：US16206292

申请日：2018-11-30

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jeffrey Douglas Gee ,  Rohan Ramanath ,  Deepak Kumar

IPC: G06F40/00 ,  G06F40/289 ,  G06Q50/00 ,  H04L29/08

Abstract: Techniques for improving the accuracy, relevancy, and efficiency of a computer system of an online service by providing a user interface to optimize a digital page of a user on the online service are disclosed herein. In some embodiments, a computer system receives a plurality of phrases for a type of job, selects a group of phrases from the plurality of phrases based on a corresponding relevancy measurement and a corresponding diversity measurement for each phrase in the selected group of phrases, and generates a recommendation for a page of a first user based on the selected group of phrases, with the recommendation comprising a suggested addition of the selected group of phrases to the page of the first user.

公开(公告)号：US20200175394A1

公开(公告)日：2020-06-04

申请号：US16206387

申请日：2018-11-30

Applicant: Microsoft Technology Licensing, LLC

Inventor： Jeffrey Douglas Gee ,  Rohan Ramanath ,  Deepak Kumar

IPC: G06N5/04 ,  G06K9/62 ,  G06Q10/06 ,  G06N3/02 ,  G06N20/10 ,  G06Q10/10

Abstract: Techniques for improving the accuracy, relevancy, and efficiency of a computer system of an online service by providing a user interface to optimize a digital page of a user on the online service are disclosed herein. In some embodiments, a computer system trains a classifier using a first plurality of training data, and then, for each one of a first plurality of sample data, generates a corresponding likelihood value indicating a likelihood that the one of the first plurality of sample data corresponds to a measurable accomplishment using the trained classifier, identifies a portion of the first plurality of sample data as corresponding to confused predictions based on the corresponding likelihood values of the portion of the first plurality of sample data and a confusion criteria, and retrains the trained classifier using a second plurality of training data that includes the portion of the first plurality of sample data.

公开(公告)号：US10346304B2

公开(公告)日：2019-07-09

申请号：US15659544

申请日：2017-07-25

Applicant: Microsoft Technology Licensing, LLC

Inventor： Liqin Xu ,  Wen Pu ,  Rohan Ramanath ,  Kun Liu

IPC: G06F12/0815 ,  G06F11/07 ,  G06F16/27 ,  G06F16/23 ,  G06F16/2455

Abstract: Techniques related to cache management for multi-node databases are disclosed. In some embodiments, a system comprises one or more computing devices including a training component, data store, cache, filtering component, and listening component. The training component produces a plurality of models based on user interaction data. The plurality of models are stored in the data store, which responds to requests from the cache when the cache experiences cache misses. The cache stores a first subset of the plurality of models. The filtering component selects a second subset of the plurality of models based on one or more criteria. Furthermore, the filtering component sends the second subset of the plurality of models to a messaging service. The listening component retrieves the second subset of the plurality of models from the messaging service. Furthermore, the listening component causes the second subset of the plurality of models to be stored in the cache.

公开(公告)号：US20190087238A1

公开(公告)日：2019-03-21

申请号：US15706225

申请日：2017-09-15

Applicant: Microsoft Technology Licensing, LLC

Inventor： Wen Pu ,  Liqin Xu ,  Rohan Ramanath ,  Kun Liu

IPC: G06F9/50 ,  G06F17/30

CPC classification number: G06F9/5088 ,  G06F9/50 ,  G06F16/2322 ,  G06Q10/00 ,  G06Q10/04 ,  G06Q10/06

Abstract: Techniques for incremental workflow execution are provided. In one technique, a computing job in a workflow identifies an input path that indicates a first location from which the computing job is to read input data. The computing job identifies an output path that indicates a second location to which the computing job is to write output data. The computing job performs a comparison between the input path and the output path. Based on the comparison, the computing job determines whether to read the input data from the first location. If the input path does not correspond to the output path, then the computing job reads the input data from the first location, generates particular output data based on the input data, and writes the particular output data to the second location. The computing job ceases to execute if the input path corresponds to the output path.

公开(公告)号：US20190034338A1

公开(公告)日：2019-01-31

申请号：US15659544

申请日：2017-07-25

Applicant: Microsoft Technology Licensing, LLC

Inventor： Liqin Xu ,  Wen Pu ,  Rohan Ramanath ,  Kun Liu

IPC: G06F12/0815 ,  G06F17/30 ,  G06F11/07

CPC classification number: G06F12/0815 ,  G06F11/073 ,  G06F16/2358 ,  G06F16/24552 ,  G06F16/273 ,  G06F2201/80

Abstract: Techniques related to cache management for multi-node databases are disclosed. In some embodiments, a system comprises one or more computing devices including a training component, data store, cache, filtering component, and listening component. The training component produces a plurality of models based on user interaction data. The plurality of models are stored in the data store, which responds to requests from the cache when the cache experiences cache misses. The cache stores a first subset of the plurality of models. The filtering component selects a second subset of the plurality of models based on one or more criteria. Furthermore, the filtering component sends the second subset of the plurality of models to a messaging service. The listening component retrieves the second subset of the plurality of models from the messaging service. Furthermore, the listening component causes the second subset of the plurality of models to be stored in the cache.