Microsoft Technology Licensing, LLC

Avinash Vemuluru

Kun Wu

Arun Sacheti

Parthasarathy Govindarajen

Paul Valentin Borza

XiaoWei Sheng

Justin Hamilton

Bing Lang

Troy Ma

Jun Liu

Yanfeng Sun

Xiaodong Fan

Diane Shambaugh

Aaron Chun Win Yuen

Karim Hasham

Malik Mehdi Pradhan

Nikita Astrakhantsev

Nektarios Ioannides

Dong Han Wang

Liang Tang

Soohoon Cho

Gautam Vishwas Vaidya

Alexander Jack Sunell

Alexandra Victoria Foote

Alexandre Michelis

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

The technology described herein provides an efficient mechanism for quickly analyzing huge amounts of media content to find media content (hereafter 'content' or 'media content') that is relevant to a user. The technology analyzes features of a curator to classify curators by interest and/or find curators with similar content recommendations. The curator data can be used to make curator recommendations to users based on the user's interests. The technology described herein collects curator data from multiple content sites and analyzes the data to identify curators that recommend similar content on different content sites.

Recommending a content curator

A representative image system is described herein that provides a representative image for any given search query. Upon receiving a search for a term (or terms), the system accesses an inverted index to identify images associated with that term. The system then receives a ranked list of images. The ranked list includes image identifiers, and once an item in the list is selected the system can use the associated image identifier to retrieve the image from a thumbnail or other server. If an editor has overridden the default image for the present search query, then the system returns the image identifier for the overridden image, which can be used to access the image from the thumbnail or other server. Thus, the representative image system provides a reliable and universal mechanism for retrieving representative images for any given topic dynamically in real time.

Dynamic definitive image service

Systems and methods for identifying a representative image for any given search query are provided. In response to a search for a query term (or terms), the system accesses an inverted index to identify images associated with that term. The system then receives a ranked list of images. The ranked list includes image identifiers, and once an item in the list is selected the system can use the associated image identifier to retrieve the image from a server. If an editor has overridden the default image for the present search query, then the system returns the image identifier for the overridden image, which can be used to access the image from the server. Thus, the representative image system provides a reliable and universal mechanism for retrieving representative images for any given topic dynamically in real time.

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Redmond, WA, United States of America

Avinash Vemuluru