Abstract: The disclosed embodiments provide a system for performing a natural language search. During operation, the system applies a first machine learning model to a natural language query to predict one or more search intentions associated with the natural language query. Next, the system applies a second machine learning model to the natural language query to produce one or more search parameters associated with a first intention in the search intention(s), wherein the search parameter(s) include a field and a value of the field. The system then performs a first search of a first vertical associated with the first intention using the search parameter(s). Finally, the system generates a ranking containing a first set of search results from the first search of the first vertical and outputs at least a portion of the ranking in a response to the natural language query.

Abstract: In various example embodiments, a system and method for modifying user input are presented. In one embodiment, a method includes receiving electronic input from a member of a social networking service, the input comprising a named entity; transmitting a query to a database of entities connected to the social networking service to select a set of entities in the database whose names are within a character edit distance of a spelling of the named entity; identifying a matching entity that is connected to the member at the social networking service and matches an entity in the set of entities; and modifying the input by replacing the spelling of the named entity with a spelling of the matching entity.

Abstract: The disclosed embodiments provide a system for performing a natural language search. During operation, the system applies a first machine learning model to a natural language query to predict one or more search intentions associated with the natural language query. Next, the system applies a second machine learning model to the natural language query to produce one or more search parameters associated with a first intention in the search intention(s), wherein the search parameter(s) include a field and a value of the field. The system then performs a first search of a first vertical associated with the first intention using the search parameter(s). Finally, the system generates a ranking containing a first set of search results from the first search of the first vertical and outputs at least a portion of the ranking in a response to the natural language query.

Abstract: In an example embodiment, one or more query terms are obtained. Then, for each of the one or more query terms, a standardized entity taxonomy is searched to locate a standardized entity that most closely matches the query term, with the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities. A confidence score is then calculated for the query term-standardized entity pair for the standardized entity that most closely matches the query term, and the query term is tagged with the entity identification corresponding to the standardized entity that most closely matches the query term and the calculated confidence score.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries using query term weighting. A search system receives a search term comprising multiple keywords and executes a search query based on the search term. In response to determining that the number of search results is less than a threshold number, the search system determines, based on historical query reformulation data, weight values for the keywords included in the search term. The weight values indicate a probability that each respective keyword would be removed when reformulating the search term. The search system generates a reformulated search term based on the weight values and executes a second search query based on the reformulated search term. The search system causes presentation of at least a portion of the search results on a client device of the requesting user.

Abstract: This disclosure relates to systems and methods for searching names using name clusters. A method includes receiving names, generating a plurality of phonetic cluster identifiers, forming a plurality of name clusters by grouping the names having an equivalent cluster id, removing names from the respective name clusters that differ from a root name by more than either a particular spelling of a phonetic sound or a specific member's reformulation according to a reformulation dictionary, and suggesting one or more names by generating a phonetic cluster id for the received name using the database of phonetic associations and returning names found in the name cluster that matches the phonetic cluster id.

Abstract: Disclosed are systems, methods, and non-transitory computer-readable media for expanding search queries using query term weighting. A search system receives a search term comprising multiple keywords and executes a search query based on the search term. In response to determining that the number of search results is less than a threshold number, the search system determines, based on historical query reformulation data, weight values for the keywords included in the search term. The weight values indicate a probability that each respective keyword would be removed when reformulating the search term. The search system generates a reformulated search term based on the weight values and executes a second search query based on the reformulated search term. The search system causes presentation of at least a portion of the search results on a client device of the requesting user.

Abstract: In various example embodiments, a system and method for modifying user input are presented. In one embodiment, a method includes receiving electronic input from a member of a social networking service, the input comprising a named entity; transmitting a query to a database of entities connected to the social networking service to select a set of entities in the database whose names are within a character edit distance of a spelling of the named entity; identifying a matching entity that is connected to the member at the social networking service and matches an entity in the set of entities; and modifying the input by replacing the spelling of the named entity with a spelling of the matching entity.

Abstract: In an example embodiment, one or more query terms are obtained. Then, for each of the one or more query terms, a standardized entity taxonomy is searched to locate a standardized entity that most closely matches the query term, with the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities. A confidence score is then calculated for the query term-standardized entity pair for the standardized entity that most closely matches the query term, and the query term is tagged with the entity identification corresponding to the standardized entity that most closely matches the query term and the calculated confidence score.

Abstract: In an example embodiment, one or more query terms are obtained. Then, for each of the one or more query terms, a standardized entity taxonomy is searched to locate a standardized entity that most closely matches the query term, with the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities. A confidence score is then calculated for the query term-standardized entity pair for the standardized entity that most closely matches the query term, and the query term is tagged with the entity identification corresponding to the standardized entity that most closely matches the query term and the calculated confidence score.

Abstract: This disclosure relates to systems and methods for searching names using name clusters. A method includes receiving names, generating a plurality of phonetic cluster identifiers, forming a plurality of name clusters by grouping the names having an equivalent cluster id, removing names from the respective name clusters that differ from a root name by more than either a particular spelling of a phonetic sound or a specific member's reformulation according to a reformulation dictionary, and suggesting one or more names by generating a phonetic cluster id for the received name using the database of phonetic associations and returning names found in the name cluster that matches the phonetic cluster id.

Abstract: A system and method for generating a data structure for an input query are provided. In example embodiments, the system receives an input query comprising of a plurality of terms. A data structure is generated comprising of a root node and lower level nodes, the root node indicating choices available for the query input, the lower level nodes including a first node with a first term of the input query and a second node with a second term of the input query. The first node is mapped to a first category with a first confidence score indicating a confidence of the mapping of the first node to the first category. The second node is mapped to a second category with a second confidence score indicating a confidence of the mapping of the second node to the second category.

Abstract: In an example embodiment, one or more query terms are obtained. Then, for each of the one or more query terms, a standardized entity taxonomy is searched to locate a standardized entity that most closely matches the query term, with the standardized entity taxonomy comprising an entity identification for each of a plurality of different standardized entities. A confidence score is then calculated for the query term-standardized entity pair for the standardized entity that most closely matches the query term, and the query term is tagged with the entity identification corresponding to the standardized entity that most closely matches the query term and the calculated confidence score.

Abstract: Systems and methods for searching for information within social networks are described. In some examples embodiments, a search assist system receives a query, such as a partial query, identifies two or more categories of data that include information satisfying the query, ranks the identified categories of data based on various selection criteria, and presents suggested search terms based on the rankings.

Abstract: Systems and methods for providing career recommendations to a member of a social network are described. In some example embodiments, the systems and methods receive input associated with a professional or aspirational goal from a member of a social network, determine a recommendation based on information stored by the social network, and provide the recommendation to the member of the social network, among other things.

Abstract: Systems and methods for providing career recommendations to a member of a social network are described. In some example embodiments, the systems and methods receive input associated with a professional or aspirational goal from a member of a social network, determine a recommendation based on information stored by the social network, and provide the recommendation to the member of the social network, among other things.

Abstract: Systems and methods for searching for information within social networks are described. In some examples embodiments, a search assist system receives a query, such as a partial query, identifies two or more categories of data that include information satisfying the query, ranks the identified categories of data based on various selection criteria, and presents suggested search terms based on the rankings.

Abstract: Systems and methods for searching for information within social networks are described. In some examples embodiments, a search assist system receives a query, such as a partial query, identifies two or more categories of data that include information satisfying the query, ranks the identified categories of data based on various selection criteria, and presents suggested search terms based on the rankings.