MACHINE-BASED EXTRACTION OF CUSTOMER OBSERVABLES FROM UNSTRUCTURED TEXT DATA AND REDUCING FALSE POSITIVES THEREIN

摘要

A system having an annotation module that annotates, using a master ontology, unstructured verbatim regarding a product and related issue, and a customer-observable (CO) construction module determining associations amongst terminology in the annotated output, yielding a group of CO pairs. A CO merging module merges at least one first CO pair into a second CO pair based on similarities. A pointwise mutual-information module determines which CO pairs of the group of merged CO pairs are relatively more-severe or more-relevant, yielding a group of critical CO pairs. An output module initiates activity to implement the results, such as by automated repair of the product or change to product design or manufacturing process. The system in some embodiments identifies, using a subject-matter-expert (SME) database, features of false-positive associations, and in machine-learning implements the features to improve CO formation going forward.