Microsoft Technology Licensing, LLC

Amazon Technologies, Inc.

Anthony Nino Bice

Hariharan Sivaramakrishnan

David Michael Robinson

Moe Khosravy

Emmanouil Koukoumidis

Christian Liensberger

Stephen L Lawler

Saral Jain

James P Finnigan

David Mancini

Norm Bryar

Namita Parab

Christopher Alme

Vanya Avramova

In accordance with one aspect of the present disclosure, a request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

Recommending data enrichments

Features are disclosed for providing a browsing experience for users where the browser interface and/or page layout are modified based on aggregated user preference data. Various browser modules can be exposed for a given content page based on analyzing data representing interactions of users with browser modules while viewing the content page. Accordingly, the modules exposed to users viewing the page can include useful functionalities for interacting with the content. Content page layouts can also be dynamically modified based on analyzed interactions of users with elements of the content page.

Dynamic modification of browser and content presentation

Architecture that enables the capability to more effectively define and resize geofences to provide improved geofence utility based on rich context and crowd-sourced data. The architecture enables the intelligent placement of geofences based on rich context that includes both user context and ambient context such as the (predicted or implicitly/explicitly defined) user's travel path, mode of transport, the type of the entity to be visited by the user and geofenced, and the user incentive for visiting the entity to be geofenced. The ambient context includes non-user specific information such as external conditions that may limit or thwart user mobility such as traffic and weather conditions. The rich context and crowd-sourced data assist in improving the spatiotemporal accuracy of suggested/constructed geofences thereby creating a 'shaped' geofence that is sufficiently defined to approximate the shape of the entity being geofenced with some degree of accuracy.

Geofences from context and crowd-sourcing

The present invention extends to methods, systems, and computer program products for recommending data sources. A request to provide recommendations of data enrichments for a database is received at a recommendation engine. The recommendation engine may perform static and dynamic analysis of data associated with the database and may further refine recommendations based on policies. The recommendation engine may then provide the recommendations, if any, of data enrichments to allow a software developer, for example, to indicate whether the data enrichments are to be used.

The subject disclosure is directed towards enriching database query responses using data from external data sources. When processing a database query seeking enriched data from an external data source, a request is communicated to the external data source based on the database query. An enriched database query response is generated based on data provided by the external data source. The enriched database query response may be combined with data returned via an internal database query operation, and/or inserted into a local database table.

Enriching database query responses using data from external data sources

The present invention extends to methods, systems, and computer program products for intelligently recommending schemas based on user input that defines a portion of a data structure. An intelligent auto-complete function can identify characteristics of the user input and, based on these characteristics, recommend schemas that are most likely to be selected by the user to complete the data structure or portion of the data structure. The identified characteristics of the user input can be compared to characteristics of defined schemas or of other data structures to identify schemas that are most likely to match the user's intent. These schemas are then recommended to the user. Such schemas can define the recommended shape of the data structure being defined, including data types for a particular column, columns to add to the data structure, or can define additional data structures to be added such as additional tables to a database.

Intelligently recommending schemas based on user input

Embodiments are directed to selecting and applying data-specific presentations, to adaptively selecting visual presentations based on historical data and to providing rendering hints for data presentations. In one scenario, a computer system receives an indication that a visual presentation is to be applied to a specified portion of data. The computer system analyzes the specified data to determine which of a plurality of data presentations is most relevant for the specified data. The relevance is based on relevancy factors including one or more of the following: end-user profile, structure of the specified data and patterns within the specified data. The computer system then applies the determined appropriate visual presentation to the specified data.

Dynamic visualization generation and implementation

The present invention extends to methods, systems, and computer program products for recommending data based on user and data attributes. User information and accessed data sets are periodically (and possibly automatically) accessed and updated. Source attributes are derived from user information and accessed data sets. Target attributes are derived from data directories and data services. Source attributes for an accessed data set are used along target attributes for a data directory or data service to determine the desirability of data directory or data service as a source of data relevant to the accessed data set. The data directory and/or data service can be recommended as able to provide relevant data. Accordingly, recommend relevant data can be recommended to a user without the user having to expressly search for the relevant data or even know that the relevant data exists.

Growing community of inventors

Seattle, WA, United States of America

Anthony Nino Bice