Microsoft Technology Licensing, LLC

Linkedin Corporation

Liang Tang

Jun Liu

Arun Sacheti

Anmol Bhasin

Jaewon Yang

Bee-Chung Chen

Parthasarathy Govindarajen

Baoshi Yan

Xiaodong Fan

Diane Shambaugh

Yanen Li

Lili Wu

Nektarios Ioannides

Haishan Liu

Nikita Astrakhantsev

Avinash Vemuluru

Dong Han Wang

Alexander Jack Sunell

Alexandra Victoria Foote

Elena Usinskiene

Qianyue You

Souvick Sarkar

Adam Jeffrey Curtis

Jeffrey Roger Devries

The present disclosure relates to systems, devices, and methods for a visual exploration of search engine results. The systems, devices, and methods may present, in response to receiving the search engine results for a query to perform a task, a search result webpage with a cascading waterfall layout that includes a plurality of images from a plurality of webpages included in the search results. The search result webpage may also present, adjacent to the plurality of images, structured data corresponding to a selected image from the plurality of images where the structured data includes details from the webpage to complete the task.

Image reranking and presentation for visual exploration

A news feed system provided with an on-line social network system determines that a news feed is to be constructed for a viewer. The news feed system accesses the viewer's profile and other information associated with the viewer, accesses an inventory of activities that have been identified as potentially of interest to the viewer, and calculates relevance score for each item inventory of activities using the combined coefficients methodology. The activities are then arranged for presentation to the viewer via a news feed web page, using respective calculated relevance scores.

Using combined coefficients for viral action optimization in an on-line social network

Systems and methods are disclosed that recommend one or more electronic presentations to a user based on one or more factors. These factors may include contextual information, behavioral information, profile information, or combinations of the foregoing. Contextual information may include content and/or features extracted from a given electronic presentation. Behavioral information may include user behavioral data, such as the number of times a user has viewed a presentation, the amount of the presentation viewed by the user, presentations previously viewed by the user, and other such behavioral data. Profile information may include user professional profile information, such as skills the user has identified as possessing, employment history information, and other such user professional profile information.

Providing recommendations for electronic presentations based on contextual and behavioral data

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Sunnyvale, CA, United States of America

Liang Tang