Abstract: A processing method includes obtaining character information, the character information being used to represent a search target, obtaining an image set, the image set including a plurality of images, and based on the character information, the image set, and an intelligent engine, obtaining an image search result including. Based on the character information and a first model in the intelligent engine, a first set is obtained. The first set includes a plurality of first images. Based on the first set, the image set, and a second model in the intelligent engine, a second set is obtained. The second set includes a plurality of second images, the second images is used as image search results, and the first model is different from the second model.

Abstract: Wnt signaling antagonist and agonist compositions and methods for their use are provided.

Abstract: Wnt signaling antagonist and agonist compositions and methods for their use are provided.

Abstract: 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.

Abstract: Wnt signaling antagonist and agonist compositions and methods for their use are provided.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: A social networking system allows users of the social networking system to create and join various groups maintained in the social networking system. The social networking system may partition the groups into a geographical grid based on geographic locations associated with the groups, such that each group is associated with a portion of the geographical grid. Each group is associated with one or more topics, which may be inferred by the social networking system based on content posted by members of the group in association with the group and attributes associated with members of the group. Each group is also associated with membership criteria that include attributes for members of the group. Based on the geographical grid, the topics, and/or the membership criteria associated with the groups, the social networking system may select one or more groups to recommend to a user of the social networking system.

Abstract: 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.

Abstract: There is provided a sensor network information collection mechanism in which, after a UE has decided to become part of an information collecting operation for collecting information from a local sensor network, a signaling transmitted from a managing node of a local sensor network is received and processed. A communication network control element is informed about the willingness to become an information collector by sending a report message comprising measurement results derived from the signaling received from the managing node of the local sensor network. When receiving a gateway allocation message indicating that the UE is determined to be a gateway element to the local sensor network, the information collecting operation is started wherein sensor nodes of the local sensor network are woke up, and a traffic flow direction in the local sensor network is set in accordance with the managing node identity to which the UE is accessed.

Abstract: 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.

Abstract: A method, an apparatus and a computer-readable storage medium for accessing a wireless sensor network with a multimode user equipment. The method includes a user equipment receiving broadcasted wireless sensor network information; requesting access information for the wireless sensor network from a base station of a mobile data network; receiving the access information from the base station; and accessing the wireless sensor network using said access information.

Abstract: 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.

Abstract: 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.

Abstract: 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.

Abstract: 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.