Patent application number | Description | Published |
20120011073 | Knowledge Extraction Methodology for Unstructured Data Using Ontology-Based Text Mining - A method is provided for extracting data from service repair verbatims in a vehicle service reporting system. Each service repair verbatim includes a technician's comments concerning a part, a symptom associated with the part, and a repair action associated with the symptom. Each service repair verbatim includes information relating to an identified problem with at least one vehicle part. A diagnostic and prognostic ontology database is provided that is structured by vehicle part classification, a vehicle part sub-class classification, and a relationship classification, wherein the relationship classification includes symptom relationships and action relationships. Each of the service repair verbatims are reconstructed utilizing the diagnostic and prognostic ontology database. Combinations of information are extracted from the reconstructed service repair verbatims as a function of user input criteria. A frequency is determined of each combination extracted in the reconstructed service repair verbatims. The service repair verbatims are clustered for each combination. | 01-12-2012 |
20120232905 | METHODOLOGY TO IMPROVE FAILURE PREDICTION ACCURACY BY FUSING TEXTUAL DATA WITH RELIABILITY MODEL - A method and system for developing reliability models from unstructured text documents, such as text verbatim descriptions from service technicians. An ontology, or data model, and heuristic rules are used to identify and extract failure modes and parts from the text verbatim comments associated with specific labor codes from service events. Like-meaning but differently-worded terms are then merged using text similarity scoring techniques. The resultant failure modes are used to create enhanced reliability models, where component reliability is predicted in terms of individual failure modes instead of aggregated for the component. The enhanced reliability models provide improved reliability prediction for the component, and also provides insight into aspects of the component design which can be improved in the future. | 09-13-2012 |
20120233112 | DEVELOPING FAULT MODEL FROM UNSTRUCTURED TEXT DOCUMENTS - A method and system for developing fault models from unstructured text documents, such as text verbatim descriptions from customers and service technicians. An ontology, or data model, and heuristic rules are used to identify and extract descriptive terms from the text verbatim document. The descriptive terms are then classified into types, including symptoms, failure modes, and parts. Like-meaning but differently-worded descriptive terms are then merged using text similarity scoring techniques. The resultant symptoms, failure modes, parts, and correlations are then assembled into a fault model, which can be used for real-time fault diagnosis onboard a vehicle, or off-board at service shops. | 09-13-2012 |
20120233132 | METHODOLOGY TO ESTABLISH TERM CO-RELATIONSHIP USING SENTENCE BOUNDARY DETECTION - A method and system for splitting a text document into individual sentences using sentence boundary detection, and establishing co-relationships between terms which are present in the same sentence. A document corpus, or collection of text records, is provided, containing text with terms to be extracted. The text records in the document corpus are divided into individual sentences, using a set of rules for sentence boundary detection. The individual sentences are then analyzed to extract and correlate terms, such as parts and symptoms, symptoms and actions, or parts and failure modes. The correlated terms are then validated based on frequency of occurrence, with term pairs being considered valid if their frequency of occurrence exceeds a minimum frequency threshold. The validated term correlations can be used for fault model development, document classification, and document clustering. | 09-13-2012 |
20130091139 | METHOD AND SYSTEM TO AUGMENT VEHICLE DOMAIN ONTOLOGIES FOR VEHICLE DIAGNOSIS - A document may be received at a processing module. One or more tags may be applied to the document, each tag applied to a term, each tag representing a part of speech. One or more terms may be extracted from the document based on the tag. A weighting assignment parameter may be determined for each of the one or more extracted terms. Based on the weighting assignment parameter associated with each of the extracted terms, it may be determined whether the domain ontology includes the one or more extracted terms. If the domain ontology does not include the one or more extracted terms, the domain ontology may be augmented such that the domain ontology comprises the one or more extracted terms. | 04-11-2013 |
20140258304 | ADAPTABLE FRAMEWORK FOR ONTOLOGY-BASED INFORMATION EXTRACTION - A warranty database stores service repair verbatims. An ontology database that specifies relationships between service terms includes linking relationships between vehicle terminology and cluster categories. The ontology database is reconfigurable for allowing a user to add, delete, and modify contents within the ontology database. A verbatim extraction tool extracts service repair verbatims from the warranty database as function of user selected parameters and a user selected ontology. The user selected ontology is a subset of the ontology database. The service verbatims are segregated into a plurality of cluster categories as a function of the selected parameters and the user selected ontology. A report generating device selectively generated reports based on segregating service verbatims into a plurality of cluster categories. Each respective cluster category includes associated service repair verbatims that are selected as a function of the linking relationship of terms within the service verbatim and the user selected ontology. | 09-11-2014 |
20150081729 | METHODS AND SYSTEMS FOR COMBINING VEHICLE DATA - Methods and systems are provided for automatically comparing, combining and fusing vehicle data. First data is obtained pertaining to a first plurality of vehicles. Second data is obtained pertaining to a second plurality of vehicles. The first data and the second data are compared and combined based on syntactic similarity between respective data elements of the first data and the second data collected during different stages of vehicle life cycle development. | 03-19-2015 |