Abstract: A system and a method for accessing at least one automation from an automation store are provided. The method comprises receiving a user input indicative of selection of at least one automation for accessing from a plurality of automations displayed in the automation store, and automatically uploading, in response to receiving the user input, the selected automation to a personal workspace of the user from the automation store. The automations are accessed via one or more Application Programming Interface (API) calls directed to an automation cloud server. Further, the method comprises generating a notification indicative of upload of the selected automation for accessing the automation. The uploaded automation is displayed in a software robot assistant associated with the user. Furthermore, the method comprises displaying the generated notification in an application interface associated with the automation store and displaying the selected automation in the personal workspace in the application interface.

Abstract: In one embodiment, an online social network accesses a place-entity cluster comprising a number of place-entity nodes corresponding to a particular place-entity having a geographic location. One of the place-entity nodes is identified as an initial canonical place-entity cluster connected to the other place-entity nodes by redirection edges. A cluster score is calculated for each place-entity node in the cluster, and nodes having a cluster score above a threshold is identified. One of the identified place-entity nodes is selected as a replacement canonical place-entity node. If the replacement node is different from the initial canonical node, then the place-entity cluster is updated by adding or removing at least one place-entity node from the cluster based on their respective cluster scores.

Abstract: In one embodiment, a method includes identifying and recursively populating a geographic tile with entities. Recursively populating a geographic tile with entities includes: sending a request to a third-party server for entities located near a representative point of the geographic tile; calculating a maximum distance from the representative point among the entities received; and determining whether a bounding perimeter based on the maximum distance encompasses the geographic tile. If the bounding perimeter encompasses the geographic tile, the retrieved entities located within the geographic tile are stored in association with an identifier for the geographic tile. If the bounding perimeter does not encompass the geographic tile, the geographic tile is divided and the subdivision tiles are recursively populated.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Abstract: In one embodiment, a method includes identifying and recursively populating a geographic tile with entities. Recursively populating a geographic tile with entities includes: sending a request to a third-party server for entities located near a representative point of the geographic tile; calculating a maximum distance from the representative point among the entities received; and determining whether a bounding perimeter based on the maximum distance encompasses the geographic tile. If the bounding perimeter encompasses the geographic tile, the retrieved entities located within the geographic tile are stored in association with an identifier for the geographic tile. If the bounding perimeter does not encompass the geographic tile, the geographic tile is divided and the subdivision tiles are recursively populated.

Abstract: In one embodiment, an online social network accesses a place-entity cluster comprising a number of place-entity nodes corresponding to a particular place-entity having a geographic location. One of the place-entity nodes is identified as an initial canonical place-entity cluster connected to the other place-entity nodes by redirection edges. A cluster score is calculated for each place-entity node in the cluster, and nodes having a cluster score above a threshold is identified. One of the identified place-entity nodes is selected as a replacement canonical place-entity node. If the replacement node is different from the initial canonical node, then the place-entity cluster is updated by adding or removing at least one place-entity node from the cluster based on their respective cluster scores.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.

Abstract: A social networking system generates a location store based on information received from its users. The location store includes entries having a physical location description and one or more terms associated with the physical location description. One or more entries associated with physical location descriptions within an area are identified. A local frequency of occurrence of each term in the identified entry is determined, and a global frequency of occurrence of each term in the identified entries within the location store is determined. Trending terms in the identified entries are determined based on the local frequencies and the global frequencies. Identified entries are compared to each other, with a score based on differing terms in compared entries and whether the differing terms are trending terms is generated. If a score is less than a threshold value, a combined entry is generated from the compared entries.