Abstract:
In particular embodiments, a method includes receiving, from a client device associated with a first user of an online social network, a text query comprising one or more character strings, identifying one or more data objects that match at least a portion of one or more of the character strings, wherein each of the identified data objects is connected to the first user within the online social network, generating one or more recommended queries that each comprise the character strings of the text query and references to one or more of the identified data objects, and sending, to the client device associated with the first user in response to receiving the text query, one or more of the recommended queries for display to the first user.
Abstract:
In particular embodiments, a method includes receiving an text query, identifying nodes and edges from a social graph that correspond to character strings from the text query, and then generating recommended queries that include references to the identified nodes and edges.
Abstract:
In one embodiment, a method includes receiving an unstructured text query from a first user of an online social network; and accessing, from a data store of the mobile client system, a set of nodes of a social graph of the online social network. The social graph includes a number of nodes and edges connecting the nodes. The nodes include a first node corresponding to the first user and a number of second nodes that each correspond to a concept or a second user associated with the online social network. The method also includes accessing, from the data store of the mobile client system, a set of grammar templates. Each grammar template includes one or more non-terminal tokens and one or more query tokens. The query tokens include references to zero or more second nodes and one or more edges and each grammar template is based on a natural-language string.
Abstract:
In one embodiment, a method includes receiving an unstructured text query to search for posts of the online social network. The method includes parsing the text query to identify one or more n-grams. The method includes searching an index of keyword phrases associated with the first user to identify one or more keyword phrases matching one or more of the n-grams of the text query. The index of keyword phrases is based on posts by one or more second users of the online social network. The method includes calculating a keyword score for each of the identified keyword phrases. The method includes generating one or more suggested queries. Each suggested query includes one or more n-grams identified from the text query and one or more identified keyword phrases. The method includes sending one or more of the suggested queries to search for posts of the online social network.
Abstract:
In particular embodiments, a method includes receiving an unstructured text query, identifying nodes and edges from a social graph that correspond to n-grams in the text query, generating structured queries that include references to the identified nodes and edges, receiving a selection of a structured query, identifying target nodes that correspond to the structured query, and then generating search results that include target nodes with privacy settings where the nodes and edges along the path connecting the target node and the querying user are all visible to the user.
Abstract:
In particular embodiments, a method includes receiving an unstructured text query, parsing the text query to identify n-grams; determining a score that the n-grams correspond to particular nodes and edges from a social graph, identifying those nodes and edges with a score greater than a threshold score, and then generating structured queries that include references to the identified nodes and edges.
Abstract:
In particular embodiments, a method includes receiving an unstructured text query, identifying nodes and edges from a social graph that correspond to n-grams in the text query, and then generating structured queries that include references to the identified nodes and edges.
Abstract:
In one embodiment, a method includes receiving a search query to search for multimedia objects of the online social network; searching an index to identify multimedia objects based on the search query, wherein the index indexes multimedia objects and associated keywords, each keyword being extracted from communications associated with a respective multimedia object, wherein each communication is of a particular communication-type, and wherein each identified multimedia object is indexed with keywords matching at least a portion of the search query; calculating, for each identified multimedia object, an object-score based on a communication-type of a communication from which one or more of the matching keywords were sourced; and sending instructions for presenting a search-results page to a client system, the search-results page including references to identified multimedia objects having an object-score greater than a threshold object-score.
Abstract:
Systems, methods, and non-transitory computer readable media configured to acquire data associated with a content item, the data associated with the content item including contextual information. The data associated with the content item can be provided to a model trained by machine learning. A set of hashtags associated with the content item can be determined based on the model.
Abstract:
In one embodiment, a method includes receiving, at the mobile client system, a text string inputted into a query field by a first user, accessing, from a local data store, a set of grammar templates, each grammar template comprising query tokens referencing an object stored in the local data store, generating one or more natural-language suggested queries by matching portions of the text string to query tokens of the grammar templates, each suggested query comprising references to one or more of the objects stored in the local data store and the natural-language string of the matching grammar template, calculating a cost for each grammar template based at least in part on one or more portions of text string not corresponding to one of the query tokens, and displaying one or more suggested queries to the first user, each having a calculated cost below a threshold cost value.