Facebook, Inc.

Microsoft Technology Licensing, LLC

Yi Miao

Li Ju

Bradley Ray Green

Mahmood Gulam Qadir

Pritvinath Obla

Pierre N Martin

Anubhuti Manohar

Vishal Mishra

Sizheng Chen

Jireh Yiwei Tan

Eric Carl Ertmann

Congle Zhang

Chen Wang

Kelly Jayne Mayes

The described implementations relate to an access control framework for a database system. One implementation can receive, from a user, a request for data that identifies a resource, such as a view that obtains data from a database. The implementation can check the identity of the user to identify user roles associated with the user. The implementation can identify an access policy that is associated with the resource, and a rule that is associated with the access policy and applies to the user roles associated with the user. The rule can be applied to the request for data using attributes of the access policy. For example, if the request for data is a query on a view, the query can be rewritten to apply the rule.

Access control framework

An online system provides group recommendations by applying a set of sourcing rules to identify a plurality of candidate groups and then generating scores for the candidate groups. The sourcing rules can be configured to identify a relatively small subset of the groups maintained by the online system. After the candidate groups are identified, the online system generates a score for each candidate group, ranks the candidate groups based on the scores, and sends high-ranking candidate groups to the target user to be displayed as recommended groups. As a result, the online system generates a smaller number of scores, which advantageously allows for the online system to provide group recommendations to users in a more computationally efficient manner.

Recommendations for online system groups

A social networking system selects a set of groups for presentation to a user of the social networking system. To select groups, the social networking system determines scores for various groups representing a likelihood of the user interacting with the groups. The social networking system may identify a set of groups based on interactions between the user and various groups occurring during a specific time interval and determine scores for groups in the set. When determining a score for a group, the social networking system accounts for times associated with interactions between the user and various groups. Based on the scores, one or more groups are selected and presented to the user. Additionally, the social networking system may identify a time to present the selected one or more groups to the user based on prior user interactions with various groups.

Identifying groups for a social networking system user based on interactions by the user with various groups

A social networking system selects a set of groups for presentation to a user of the social networking system. To select groups, the social networking system identifies candidate groups and selects the set of groups from the candidate groups. To identify certain candidate groups, the social networking system determines a location associated with various groups based on locations associated with users included in the group. For example, the social networking system determines a centroid of a group based on locations associated with users included in the group and associates the centroid with the group if at least a threshold percentage of distances between locations associated with users included in the group and the centroid do not exceed a threshold distance. Groups associated with locations within a threshold distance of a location associated with the user are identified as candidate groups.

Identifying groups for recommendation to a social networking system user based on user location and locations associated with groups

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Redmond, WA, United States of America

Yi Miao