Microsoft Technology Licensing, LLC

Danny B Lange

Xiong Zhang

Hung-Chih Yang

Graham Arthur Wheeler

Joseph Futty

Bhalchandra Pandit

Didier Coussemaeker

Ashley Nathan Feniello

Nicolas Mai

Jason J Joyce

Adrien Felon

David M Moore

Matthew Graham Dyor

Miller Thomas Abel

Steven William Macbeth

Cynthia Dahl Wessling

Zhaowei (Charlie) Jiang

Joe Futty

A system includes a processing device configured to execute instructions including accessing messages sent by a first user and other users. The instructions include identifying a first subset of messages that were sent by the first user and identifying a second subset of messages that are related to a first topic and were sent by the first user. The instructions include determining an authority value based on counts of the first and second subsets. The instructions include identifying a third subset of messages that resulted from the other users forwarding the second subset. The instructions include determining a power value based on a count of users that sent the third subset and computing an impact score for the first user on the first topic based on the authority and power values. The instructions include, based on the impact score, contacting the first user in relation to the first topic.

Computer system for automated assessment at scale of topic-specific social media impact

An application feature store may be integrated with an application. The feature store may be accessed by a user through a feature storefront hosted within the application. The user may search the feature store for additional desired features available for the augmentation of the productivity application.

Integrated application feature store

An application store tastemaker recommendation service determines experts within a user's social network(s), receives recommendations from the experts, filters and/or ranks mobile application query results based at least in part on the recommendations. Additionally, the service may further determine the experts based on data compiled about previous actions, reviews, comments, etc., of the experts. Further, the service may provide recommendations to the user to aid in selecting mobile applications for purchase, and may provide an avenue for completing such purchases.

Application store tastemaker recommendations

A system includes a memory storing a dataset representing a community of users of a social networking service, the social networking service providing a platform enabling a user within the community to communicate with at least one of a plurality of other users within the community. The system includes a processor coupled to the memory, the processor configured to determine a ranking of the service users in the dataset based on an initial influence score for at least one of the users. The processor is also configured to determine a contribution to a first user within the community by at least one second user of the plurality of other users within the community, and calculate an influence score for the first user. The ranking is revised based at least in part on the calculated influence score, and information is rendered to a target user based on the revised ranking.

Identifying influential users of a social networking service

A canopy clustering process merges at least one set of multiple single-center canopies together into a merged multi-center canopy. Multi-center canopies, as well as the single-center canopies, can then be used to partition data objects in a dataset. The multi-center canopies allow a canopy assignment condition constraint to be relaxed without risk of leaving any data objects in a dataset outside of all canopies. Approximate distance calculations can be used as similarity metrics to define and merge canopies and to assign data objects to canopies. In one implementation, a distance between a data object and a canopy is represented as the minimum of the distances between the data object and each center of a canopy (whether merged or unmerged), and the distance between two canopies is represented as the minimum of the distances for each pairing of the center(s) in one canopy and the center(s) in the other canopy.

Grouping documents and data objects via multi-center canopy clustering

This patent relates to a system for identifying influential users of a social network platform. The system may access records of messages sent or received by a plurality of users. The system can determine a power of a user to reach other users based at least in part on the messages. The system can determine an authority of the user on a topic. The system can also compute an impact score that reflects both the power and the authority of the user on the topic. Such scores may be used to select users based on impact as part of social trend analysis, marketing or other functions.

Social media impact assessment

A system for identifying influential users of a social network platform. The system may compute a score for each of multiple users. Such a score may be topic-based, leading to a more accurate identification of influential users. Such a topic-based score may indicate authority and/or impact of a user with respect to a topic. The impact may be computed based on authority combined with other factors, such as power of the user. The authority score may be simply computed, in whole or in part, directly from a tweet log without, for example creating a retweet graph. As a result, the scores may be computed, using MapReduce primitives or other constructs that allow the computations to be distributed across multiple parallel processors. Such scores may be used to select users based on impact as part of social trend analysis, marketing or other functions.

Technologies pertaining to computing a metric that is indicative of whether an n-gram in a large corpus of text is a collocation are described herein. The metric is computed in connection with a distributed computing framework, wherein n-grams of varying lengths can be analyzed in a single input data pass, and wherein secondary sorting functionality of the distributed computing framework need not be invoked.

Identifying collocations in a corpus of text in a distributed computing environment

Techniques for identifying influential users of a social networking service are provided. Influential users may be identified via an algorithm in which an influence score is assigned to each user based at least in part on other members of the community users having taken an affirmative step with respect to the user's communications. Iterative processing may be performed, with each user's influence score being determined by contributions from other users, and each contribution being determined by the contributor's influence score as of a prior iteration. A map-reduce framework may be employed, with data representing the community being partitioned into a plurality of discrete shards, a map process corresponding to each shard calculating an influence score for users represented in the shard, and reduce processes ranking users according to influence score across all shards.

Multi-center canopy clustering

To accommodate different types and versions of execution environments on mobile devices, requests for applications from a programmable device, such as a smart phone or other mobile device include status data about the characteristics of the device. Information about the display, memory, storage, and/or script engine may be forwarded with a request. At a fulfillment server, the information is evaluated so that an appropriately versioned and configured application can be custom built, or selected from a pre-built inventory of applications. This allows a user to postpone an upgrade and still receive appropriate versions of executable, optimized to the particular mobile device.

Device dependent on-demand compiling and deployment of mobile applications

An application store tastemaker recommendation service is usable to determine experts within a user's social network(s), receive recommendations from the experts, and filter and/or rank mobile application query results based at least in part on the recommendations. Additionally, the service may be usable to determine experts based on data compiled about previous actions, reviews, comments, etc., of the experts. Further, the service may be usable to provide recommendations to the user to aid in selecting mobile applications for purchase, and may provide an avenue for completing such purchases.

This disclosure describes data conversion and techniques for sending and receiving data at a mobile device. In one implementation, a proxy server may receive data from a mobile device. The proxy server may convert the data and send the converted data to a network service. In another implementation, a mobile device may convert data and send that data to a network service. The network service may generate data in response and send that data to the mobile device directly.

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Sammamish, WA, United States of America

Danny B Lange