Microsoft Technology Licensing, LLC

Mikhail Obukhov

Qi He

Jaewon Yang

Xiao Yan

Deepak Agarwal

Bee-Chung Chen

Lin Zhu

Joey Bai

Farzard Eskafi

Shiqi Wu

Apparatuses, computer readable medium, and methods are disclosed for verifying skills of members of an online connection network. The apparatus, computer readable medium, and methods may include a method including responding to a first member of the online connection network indicating a skill possessed by the first member by selecting a skill verification user interface (UI) to present to a second member of the online connection network where the first member and the second member are connected via the online connection network. The method may further include presenting the skill verification UI to the second member, where the skill verification UI presents an indication of the first member, an indication of the skill, and a query regarding a competence level of the skill possessed by the first member. The method may further include receiving a response to the query and determining a skill validation value of the skill for the first member based on the response and a machine learning model.

Skill validation

Techniques for selecting candidates using a personalized model are disclosed herein. In some embodiments, a computer system, for each candidate of a plurality of candidates, generating a corresponding confidence score for a combination of the candidate, a particular viewer, and a particular attribute based on a scoring model, with the corresponding confidence score being configured to indicate a likelihood that the particular viewer will select the corresponding candidate as a preference with respect to the particular attribute. The computer system then selects a subset of the plurality of candidates based on the corresponding confidence scores of the candidates in the subset, and causes the subset of candidates to be displayed on a computing device of the viewer along with a prompting for the viewer to select one of the selected subset of candidates as the preference with respect to the particular attribute.

Candidate selection using personalized relevance modeling system

A system and method of adjusting an affinity score between an entity pair in a social network is disclosed. The method may include determining, with a processor, whether a first member of the entity pair is a heavy user member. The method further includes if the first member is the heavy user member, determining, with the processor, an affinity adjustment factor between the first member and the second member, and adjusting, with the processor, the affinity score between the first member and the second member of the entity pair in accordance with the adjustment factor to determine an adjusted affinity score. The method may include determining, with the processor, whether a number of interactions on content items indicates that the first member is the heavy user member. The second member is associated with a content item that is being considered for display to the first member.

Adjusting heavy users' affinity for heavy user entity-pairs in a social network

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Mountain View, CA, United States of America

Mikhail Obukhov