The Boeing Company

Krishna Srinivasmurthy

Ahmad R Yaghoobi

Temourshah Ahmady

Kjersta Lynn Larson-Smith

Matthew H Mellin

Edward R Greene

Sema Ustuntas

Kris Fantin Nunes

Examples are disclosed herein that relate to detecting product requirements within a digitized document. One example provides a method comprising: identifying a first page as a summary page, the first page comprising a keyword that refers to a second page; and detecting in the first page a first instance of a pattern comprising a first text block adjacent to a first line. A first part name and a first requirement for a first part are extracted from the first text block. In the first page, a second instance of the pattern is detected comprising a second text block adjacent to a second line. The keyword and a second part name are extracted from the second text block. The second part name and a second requirement for a second part are extracted from the second page. The first requirement and the second requirement are output for storage in a data store.

Detecting requirements for a product

A method, apparatus, system, and computer program product for applying a color to an aircraft. The color for an exterior surface of the aircraft is determined by the computer system from a design of the aircraft. A position of the color in three-dimensional space is determined by the computer system. The position is in a color space coordinate system. An inkjet printer in the inkjet printers with a point cloud in the plurality of point clouds having a smallest Euclidean distance to the position of the color is selected by the computer system. The inkjet printer is used to apply the color on the exterior surface of the aircraft.

Aircraft inkjet printing

A method for training a filter-based text recognition system for cataloging image portions associated with files using text from the image portions, the method comprising: receiving a first set of text represented in a first image portion associated with a first file; classifying the first image portion into a predetermined group, wherein the classifying is based at least in part on the first set of text; extracting a first set of features from the first set of text; harmonizing existing data in the predetermined group with the first set of text to modify the first set of features; categorizing the first set of text; and determining analytics-based rules based at least in part on the first set of features.

Natural language processing (NLP) pipeline for automated attribute extraction

Growing community of inventors

Bothell, WA, United States of America

Krishna Srinivasmurthy