Microsoft Technology Licensing, LLC

Deepak Kumar

Jeffrey Gee

Rohan Ramanath

Michael Joseph Healy

Gungor Polatkan

Kenneth Mark Osborne

Konstantin Salomatin

Gopal Parupudi

David C James

Mahesh Subhash Joshi

Ajay P Chitturi

Arijit Basu

Shivani Rao

Aditya Makarand Desai

Ilya Kleyman

Manoj Swaminathan

Ghassan G Salloum

Yen Ping Yu

Arlie L Davis

Gaurav Bhandari

Brian Anger

Daniel N J Drew

Sridhar Srinivasan

Tao Wang

Anmol Bhasin

Xiao Li

Satish Joseph Thomas

Rupesh Gupta

Shipeng Yu

Zhonghua Chu

John Leo Ellis

Sara Smoot Gerrard

Fares Hedayati

Benjamin T Grover

Onkar Anant Dalal

Jieying Chen

Lingjie Weng

David Reinhold

Roberto De Lira Garza

Kyrylo Val

Yulia Astakhova

Jiaqi Ge

Richard Moerloos

Scott Khamphoune

Ashima Jain

Himanshu Khurana

Vasudeva Nagaraja

Bhaskaran Devaraj

Vijay Ramamurthy

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.

Recommendations using session relevance and incremental learning

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.

Phrase extraction for optimizing digital page

The video recommendation system provided with an on-line connection system generates on-line video recommendations using collaborative filtering for clusters of member profiles. The recommendation system clusters member profiles using member profile information as clustering criteria. The video recommendations are then generated for a given cluster, based on aggregation of video viewing history recorded for the member profiles that are in the given cluster, using the video similarity matrix. In order to produce video recommendations for a particular member profile, the recommendation system first determines cluster membership for the member profile, retrieves recommendations generated for that cluster, and provides recommendations to the associated member. A user interface including references to one or more recommended videos is rendered on a display device of a viewer.

Cluster-based collaborative filtering

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, and then, for each one of the plurality of phrases, selects a corresponding section of a page of a first user to suggest for placement of the phrase from amongst a plurality of sections using a placement classifier, and generates a corresponding recommendation for the page of a first user based on the phrase and the determined corresponding section of the page of the first user, with the recommendation comprising a suggested addition of the phrase to the determined corresponding section of the page of the first user.

Phrase placement for optimizing digital page

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 identifies job postings published on an online service as corresponding to a type of job based on feature data of each one of the job postings, extracts phrases from the identified job postings based on a corresponding relevancy measurement and a corresponding diversity measurement for each one of the phrases, determines a corresponding section of a page of a user to suggest for placement of the extracted phrase using a placement classifier for each one of the extracted phrases, and generates a corresponding recommendation for the page based on the extracted phrase and the determined section of the extracted phrase for each one of the phrases.

User interface for optimizing digital page

The recommendation system provided with an on-line connection system identifies on-line recommendations of videos and generates a user interface (UI) by including into the resulting presentation selected recommendations of videos. The recommendations of videos presented in the UI are organized into groups that are topically coherent, where each group is decorated with a context annotation&#x2014;an explanation of why the recommendations in a given carousel are relevant for a member. Each video that is being evaluated by the recommendation system with respect to a subject member profile is assigned an annotation that is selected from a plurality of potentially applicable annotations. The technical problem of optimizing an order of presentation of recommendations grouped by context annotations, in a UI where annotations drive the layout, is addressed by deriving ranks for different context annotations based on global and personalized click through rates and using these values assigned to respective context annotations in constructing the UI.

Ranking carousels of on-line recommendations of videos

A configuration architecture automatically links the output of a business process modeler to a business system configuration tool. The output of the business process modeler is translated into a representation of a source business process that is used by the business system configuration tool to automatically generate configuration templates. A user can provide configuration information through the configuration templates. The configuration inputs are applied to an implementation of a business system to obtain a configured, working business system instance with the same functionality as the source business process.

Automatic configuration of a computer system based on process modeling of an implemented process

A machine may be configured to detect an anomalous event based on metrics pertaining to a production system. For example, the machine analyzes a time series of values associated with a metric pertaining to a production system. The machine identifies a pattern associated with the time series based on the analysis of the time series. The pattern may describe an occurrence of particular values at particular timestamps of the time series. The machine determines a range of potential values for a next timestamp in the time series based on the pattern. The machine assigns a score value to an actual value associated with the metric and corresponding to the next timestamp. The assigning of the score value may be based on a comparison of the actual value and the range of potential values. The machine identifies the actual value as a candidate for an alert based on the score value.

Anomalous event detection based on metrics pertaining to a production system

Techniques to prioritize and optimize the execution of upgrade operations are described. A technique may include determining the size of data blocks that are to be copied from one storage medium to another, and the dependencies of upgrade tasks on the data blocks and on other tasks. A task may be prioritized according to a weight that includes the cumulative sizes of the data blocks that it and its dependent tasks depend on. A data block copying may be prioritized according to the cumulative weights of the tasks that depend on that data block. Some embodiments may perform several data copying and/or tasks in parallel, rather than sequentially. Other embodiments are described and claimed.

Techniques to optimize upgrade tasks

In one embodiment, a digital asset testing systemmay test a digital assetbefore posting at a digital distribution store. A communication interfacemay receive a digital asset. A processormay execute testing of the digital asseton a testing virtual machineof a virtual machine set. The processormay execute testing of the digital assetsimultaneous with testing executed on each virtual machineof the virtual machine set. The processormay delay testing of the digital asseton the testing virtual machineif a testing virtual machine configurationis stale.

Optimizing system usage when running quality tests in a virtual machine environment

An application for which approval is requested is identified and multiple automated tests are applied to the application in groups of automated tests. Each of the groups of automated tests includes multiple ones of the multiple automated tests. If one or more automated tests in a group of automated tests returns an inconclusive result, then a manual check is initiated for the application based on the one or more automated tests that returned the inconclusive result. If one or more automated tests in a group, or a manual test applied in the manual check, returns a fail result then an indication that the application is rejected is returned, the indication that the application is rejected including an identification of why the application is rejected. If none of the multiple automated tests returns a fail result, then a manual testing phase is initiated.

Managing automated and manual application testing

A method and system for converting source tables of a database of the application to target tables of a new version of the database while reducing the amount of time that the database needs to be open in single-user access mode is provided. A conversion system divides the conversion into a multi-user phase and a single-user phase. During the multi-user phase, the conversion system can perform most of the conversions while the database is opened in multi-user access mode. The conversion system stores the converted data in auxiliary tables, rather than updating the source tables. During the single-user phase, the conversion system performs the remaining conversions and copies data from the source tables and the converted data from the auxiliary tables to the target tables.

Conversion of an application database to minimize time in single-user access mode

Systems and methods for automatic client management authority assignment are described. In one aspect, it is determined that a network management point has not been configured for a client. Responsive to this, a directory service is requested to automatically assign a site code to the client. The automatically assigned site code identifies the management point through which the client can obtain management service(s).

Automatic client management authority assignment

The present disclosure relates to mapping, tracking, and distributing policy to client devices. Policy, in particular lists of policy assignments are sent to client devices. A determination is made as to the changes or deltas between policy assignments that have been sent to client devices and policy assignments that must be sent to client devices. Identifying the delta policy assignments avoids the need be sent to client devices. Identifying the delta policy assignments avoids the need to send policy assignments that have not change and do not need to be sent to client devices. A server computer determines applicability of policy assignments to particular client devices, tracks if and when policy assignments have been deleted and allows the client to either receive a partial list of policy assignments that are required to update policy or a full list of policy assignments. Full, partial or not list policy assignment depends when a particular client device was last provided a policy assignment.

Using deltas for efficient policy distribution

Growing community of inventors

Kirkland, WA, United States of America

Deepak Kumar