Abstract: In one embodiment, a method includes receiving, from a client device of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network, parsing the structured query to identify a first query constraint and one or more second query constraints, identifying an inverse constraint associated with the first query constraint, wherein the first query constraint has been previously flagged as identifying greater than a threshold number of objects, and generating a query command based on the structured query, wherein the query command comprises the inverse constraint and the one or more second query constraints.

Abstract: In one embodiment, a method includes receiving, from a client system of a first user, a structured query comprising references to one or more selected objects accessible by the computing device, generating one or more search results corresponding to the structured query, wherein each search result corresponds to a particular object accessible by the computing device, determining one or more search intents based at least on whether one or more of the selected objects referenced in the structured query match objects corresponding to a search intent indexed in a pattern-detection model, and scoring the search results based on one or more of the search intents.

Abstract: In one embodiment, a method includes receiving from a first user of an online social network a search query, searching data stores to identify objects that match the search query, where identifying the objects is also based in part on the privacy setting for each object, determining for each identified object a visibility of the object with respect to the first user, and generating one or more search results corresponding to the search query.

Abstract: In one embodiment, a method includes receiving, from a client system of a first user of an online social network, a structured query comprising references to one or more selected objects associated with the online social network, generating a query command based on the structured query, wherein the query command comprises an inner query constraint and an outer query constraint, identifying a first set of objects matching the inner query constraint and at least in part matching the outer query constraint, identifying a second set of objects matching the outer query constraint, and generating one or more search results based on the first and second sets of objects, wherein each search result corresponds to an object of the plurality of objects.

Abstract: In one embodiment, one or more computing devices receive, from a client device of a first user, a query from the first user. The computer devices search a social graph to identify one or more nodes of the social graph that are relevant to the query. The computer devices obtain a static rank for each identified node. The static rank is based at least in part on a number of edges of a particular edge type that are connected to the node in the graph or attributes of edges connected to the node in the graph. The computer devices send to the client device of the first user for display, a search-results page responsive to the received query. The search-results page includes reference to one or more nodes having a static rank greater than a threshold rank.

Abstract: In one embodiment, one or more computing devices receive, from a client device of a first user, a query from the first user. The computer devices search a social graph to identify one or more nodes of the social graph that are relevant to the query. The computer devices obtain a static rank for each identified node. The static rank is based at least in part on a number of edges of a particular edge type that are connected to the node in the graph or attributes of edges connected to the node in the graph. The computer devices send to the client device of the first user for display, a search-results page responsive to the received query. The search-results page includes reference to one or more nodes having a static rank greater than a threshold rank.

Abstract: In one embodiment, a method includes a computing system receiving a query from a first user, which can be parsed to identify i conditions associated with the query. The system may then identify one or more search results substantially matching the i conditions. Each search result may be associated with a feature vector of j features. The system may then access a conditioned ranking model that comprises j scoring functions for each i condition. The j scoring functions may correspond to j features of the feature vectors. A score for each search result may be calculated based on the i conditions and the j features. The system may then receive a selection of one of the search results from the first user, and in response modify one or more of the j scoring functions of the conditioned ranking model based on the selection.

Abstract: In one embodiment, one or more computing devices receive, from a client device of a first user, a query from the first user. The computer devices search a social graph to identify one or more nodes of the social graph that are relevant to the query. The computer devices obtain a static rank for each identified node. The static rank is based at least in part on a number of edges of a particular edge type that are connected to the node in the graph or attributes of edges connected to the node in the graph. The computer devices send to the client device of the first user for display, a search-results page responsive to the received query. The search-results page includes reference to one or more nodes having a static rank greater than a threshold rank.

Abstract: In one embodiment, a method includes accessing a set of queries of an online social network received from one or more users of the online social network, parsing each query using a parsing algorithm to generate a query command based on each query, each query command comprising one or more query constraints for a specified number of objects of a specified object-type as specified by parsing-configuration parameters of the parsing algorithm, retrieving the specified number of objects that match at least a portion of the query constraint from one or more data stores associated with the online social network, scoring each retrieved object based on a scoring algorithm, and generating one or more revised parsing-configuration parameters based on a comparison of the scores of the retrieved objects and the specified number of objects of the query constraints.

Abstract: In one embodiment, one or more computing devices assign each of a plurality of nodes of a graph of a social-networking system to one of a plurality of search indices. Each search index corresponds to a node type, and each node assigned to a search index is of the node type that the search index corresponds to. For each search index, the one or more computing devices determine a value for each node assigned to the search index based at least in part on edges connected to the node in the graph and rank the nodes assigned to the search index based at least in part on their values. The one or more computing devices provide the search indices for storage to facilitate responding to queries encompassing objects represented by the nodes assigned to the search indices.

Abstract: In one embodiment, a method includes receiving from a first user of an online social network a search query, searching data stores to identify objects that match the search query, where identifying the objects is also based in part on the privacy setting for each object, determining for each identified object a visibility of the object with respect to the first user, and generating one or more search results corresponding to the search query.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, receiving from a user a structured query comprising references to selected nodes and selected edges, generating search results corresponding to the structured query, determine a search intent based on the selected nodes or selected edges referenced in the structured query, and scoring the search results based on the search intent.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, receiving from a user a structured query comprising references to selected nodes and selected edges, parsing the structure query to identify a first query constraint and one or more second query constraints, identifying a inverse constraint associated with the first query constraint, and generating a query command based on the structured query, where the query command includes the inverse constraint and the one or more second query constraints.

Abstract: In one embodiment, a method includes accessing a social graph that includes a plurality of nodes and edges, receiving from a user a structured query comprising references to selected nodes and selected edges, generating a query command based on the structured query based on the structured query comprising a first query constraint and a second query constraint, identifying a first set of nodes matching the first query constraint and at least in part matching the second query constraint, identifying a second set of nodes matching the second query constraint, and generating search results based on the first and second set of nodes.

Abstract: In one embodiment, one or more computing devices assign each of a plurality of nodes of a graph of a social-networking system to one of a plurality of search indices. Each search index corresponds to a node type, and each node assigned to a search index is of the node type that the search index corresponds to. For each search index, the one or more computing devices determine a value for each node assigned to the search index based at least in part on edges connected to the node in the graph and rank the nodes assigned to the search index based at least in part on their values. The one or more computing devices provide the search indices for storage to facilitate responding to queries encompassing objects represented by the nodes assigned to the search indices.

Abstract: A social networking system selects advertisements for its users using collaborative filtering based on the users' interactions with objects in the social networking system. The objects may be games, pages, groups, deals, messages, content items, advertisements, or any other object with which a user may interact in the system. The system may identify a viewing user's interaction with a first object, determine a second object that is similar to the first object based on interactions of users with both of the objects, and send an advertisement associated with the second object to the viewing user. The system determines a second object based a similarity score between the first object and the second object, which may be a measure of users who have interacted with both objects and may be normalized by a number of user interactions by the users with the objects.

Abstract: A social networking system infers a user's present interests based on the user's recent actions and/or the recent actions of the user's connections in the social networking system. The social networking system also determines a set of concepts associated with each of a set of information items, such as advertisements. By matching the user's present interests with the concepts associated with the information items, the social networking system selects one or more of the information items that are likely to be of present interest to the user. At least one of the matched interests and concepts are not identical. The social networking system then presents the selected information items for display to the user, thereby providing information based on an inferred temporal relevance of that information to the user.

Abstract: A social networking system infers a user's present interests based on the user's recent actions and/or the recent actions of the user's connections in the social networking system. The social networking system also determines a set of concepts associated with each of a set of information items, such as advertisements. By matching the user's present interests with the concepts associated with the information items, the social networking system selects one or more of the information items that are likely to be of present interest to the user. The social networking system then presents the selected information items for display to the user, thereby providing information based on an inferred temporal relevance of that information to the user.