Verizon Patent and Licensing Inc.

Jonathan Harahush

Chad Kearney

Andrew Batta

Carolyn Vlach

John Coster

Bryan Jeffrey Kobler

An exemplary query parsing system accesses user input text representative of a search query. The system generates a plurality of candidate parses of the user input text. Each of the plurality of candidate parses includes a candidate what portion and a candidate where portion determined from the user input text. The system generates a score for each candidate parse in the plurality of candidate parses based on whether one or more of a plurality of predefined parsing features are found in the respective candidate parse and on a machine learning mode. The system selects, from the plurality of candidate parses based on the scores for the plurality of candidate parses, the candidate what portion and the candidate where portion of a particular candidate parse included in the plurality of candidate parses as search parameters for the search query. Corresponding methods and systems are also disclosed.

Methods and systems for determining search parameters from a search query

A device can include one or more processors to: receive a query; determine a plurality of candidate samples based on the query, a candidate sample, of the plurality of candidate samples, having a location portion of zero or more tokens and an objective portion of zero or more tokens; determine a score for the candidate sample based on a data structure, the score being determined based on at least one of: a location value, associated with the location portion, that is identified using the data structure, or an objective value, associated with the location portion, that is identified using the data structure; and perform an action with regard to the query based on the score.

Location query processing and scoring

A device can obtain location information that includes a set of location name values associated with a set of locations. The device can identify, using a natural language processing model, a set of proper noun values associated with the set of location name values. The device can generate a set of search criteria variant terms for the set of proper noun values. The set of search criteria variant terms can each include one or more characters associated with an alias of a particular proper noun value. The device can receive, from a user device, partial search criteria relating to an alias of a destination location. The device can process the partial search criteria using the set of search criteria variant terms to identify a set of candidate search terms. The device can provide the set of candidate search terms to the user device.

Automatic generation of variations of search criteria for use in a predictive search engine

A device can receive input indicating an intersection of two or more roads. The device can identify the two or more roads included in the input using an indicator. The device can determine a geographic location of another device using information that identifies the geographic location received from the other device. The device can identify a data structure that includes information identifying a set of intersections associated with the geographic location. The device can perform a search of the two or more roads using the information identifying the two or more roads and the information included in the data structure. The device can determine a priority for one or more results of the search for the intersection after performing the search of the two or more roads. The device can provide the one or more results of the search for the intersection to permit and/or cause an action to be performed.

Predictive intersection search

An exemplary point-of-interest identification system accesses data for a point-of-interest. The system generates a plurality of scores for the point-of-interest based on one or more of a plurality of predefined features found in the data for the point-of-interest and on a machine learning model. The system selects, based on the plurality of scores, a primary point-of-interest type for the point-of-interest. The system includes the selected primary point-of-interest in a dataset for the point-of-interest. Corresponding methods and systems are also disclosed.

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Golden, CO, United States of America

Jonathan Harahush