US 12,217,135 B1
Systems and methods for building automotive repair service domain models for processing automotive repair service enterprise data
Tilak B Kasturi, Palo Alto, CA (US); Hieu Ho, San Jose, CA (US); and Aniket Dalal, Pune (IN)
Assigned to PREDII, INC., Palo Alto, CA (US)
Filed by Predii, Inc., Palo Alto, CA (US)
Filed on Oct. 27, 2018, as Appl. No. 16/172,759.
Application 16/172,759 is a continuation of application No. 14/533,085, filed on Nov. 4, 2014, granted, now 10,157,347.
Claims priority of provisional application 61/899,868, filed on Nov. 4, 2013.
This patent is subject to a terminal disclaimer.
Int. Cl. G06N 20/00 (2019.01); G06F 16/332 (2019.01); G06F 16/35 (2019.01)
CPC G06N 20/00 (2019.01) [G06F 16/3322 (2019.01); G06F 16/3326 (2019.01); G06F 16/3344 (2019.01); G06F 16/35 (2019.01)] 20 Claims
OG exemplary drawing
 
1. A method for automotive repair service enterprises, the method comprising:
building an automotive repair service domain model for processing data specific to an automotive service enterprise, the automotive service domain model comprising:
a first set of features for the automotive repair service enterprise,
a plurality of lists comprising at least one of an apriori knowledge and an aposteriori knowledge, the apriori knowledge comprising a set of predefined results, the aposteriori knowledge comprising expert training, and
a first set of rules comprising conditions for applying an action;
applying historical automotive repair service enterprise data and contextual automotive repair service data to the automotive repair service domain model to build hierarchical relationships annotated with the contextual automotive repair service data;
sending said historical automotive repair service enterprise data and/or said contextual automotive repair service data to one or more of an importer module, an extraction module, a learning module, a classification module, a feedback module, a scoring module, and/or an export module;
wherein said historical automotive repair service enterprise data comprises automotive repair service information, as well as one or more of customer information, transaction information, support request information, automotive repair information, model year, make, model, submodel, engine, odometer, trouble code information, diagnostic code information, vehicle diagnostic information, service repair data, customer transactional data, information about symptoms, information about diagnoses, information about recommended actions, information about repairs, information about parts, information about problem reporting, automotive service records, service orders, and/or experience-based service information;
extracting automotive repair service features of interest from the annotated entity relations defined in the automotive service domain model;
creating a first set of vectors by using the automotive repair service domain model, the first set of vectors relating to the first set of features and the first set of rules;
classifying and clustering the automotive repair service features to develop automotive service metadata;
storing the automotive service metadata for use by the automotive repair service domain model; and
receiving and applying expert feedback on automobile component feature extraction and symptom relationships and repair automobile service to improve the automotive repair service domain model.