Microsoft Technology Licensing, LLC

Paul Baecke

Malik Mehdi Pradhan

Alexander Leo Campbell

Robert David Frye

Kimberly A Wilton

Gustavo M C Guerra

Sean O Lyndersay

Jason Craig Nelson

Parul Manek

Gaurav S Anand

Ganesh Pandey

David Joel Sheldon

Shankaranand Arunachalam

Mark Blelock Atherton

Peter Richard Bailey

Robert Allen Lowe

Michele Banko

Xiaoqin Zhu

Daniel Hill

Gaurav Sunil Anand

Nathan Novielli

Yan Zhong

Dheeraj Mehta

Systems and methods are disclosed for dynamic search interfaces. In one implementation, a search query is received from a user within a content retrieval interface. The search query is processed with respect to a first content source to determine a relevance of the first content source with respect to the search query. Based on a determination that the first content source exceeds a defined relevance threshold, content from the first content source is requested and/or received. The content received from the first content source is presented within the content retrieval interface.

Dynamic search interfaces

In a multi-tenant computing system, a cross-tenant user search system receives a user search input from a user using a client of a first tenant. The cross-tenant user search system accesses a policy that identifies one or more related tenants that are related to the first tenant. The policy also identifies directory records of users in the related tenant that can be searched by users of the first tenant. The cross-tenant user search system executes a search against a directory for the first tenant and executes a separate search against the directory records in the related tenants, identified in the policy. The search results from searching the directory for the first tenant and the related search results from searching the directory records in the tenant are aggregated into an aggregated set of search results which are then returned to the client.

Cross-tenant people search in a multi-tenant computing system

Representative embodiments disclose mechanisms to improve the perceived responsiveness of a search engine. As a user types a query prefix into a browser or other interface to the search engine, the search engine returns query completion suggestions to the browser. The query completion suggestions, user history, user favorites and/or other information are presented to a trained machine learning model on the client device to predict a desired location that the user is attempting to navigate to. When the confidence level of the predicted location surpasses a threshold, content from the desired location is preloaded into a hidden tab in the browser. When the user submits a query, the browser submits feedback to a system responsible for updating and refining the machine learning model. Updated machine learning model coefficients can be received by the browser from the system to make predictions more accurate.

Machine learning model to preload search results

Architecture presents in a display related content in association with (an annotation) a social media post, as derived from post information of the social media post itself. The related content can be presented in the user interface proximate the social media post or elsewhere in the user interface. The related content can be presented as search engine queries, images, videos, and/or links to related websites. More specifically, the disclosed architecture facilitates the automated annotation of a social media post with related content derived from: post information such as a URL (uniform resource locator) referred to in the social media post, post information such as the text, image(s), and/or video content in a social media post itself, and post information such as content linked-to by a URL referred to in a social media post.

Generation of related content for social media posts

Systems, methods, and computer-readable storage media for providing query-completion suggestions that include answers to the complete queries suggested while the user is formulating a search query. At least a portion of a search query is received by the search engine. As the portion of the search query is received, query-completion suggestions are identified and answers to the plausible search query completions are identified for inclusion in the search input area. Upon selection of a query-completion suggestion, the search engine results page is presented, wherein the search engine results page includes the answers in the snippets generated for the results that contain the answers to the completed queries suggested to the user.

Coherent question answering in search results

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Paul Baecke