The Boeing Company

Stephen P Jewett

John M Boggio

Kenneth D Bouvier

Eric Lee Nicks

William E Wojczyk, Jr

Andrew Wall

Thomas J Hollerich

Techniques are described for analyzing text. Embodiments tokenize a plurality of documents into a plurality of sets of terms. An average top dimension weight corresponding to the plurality of documents is calculated based on performing singular value decomposition (SVD) factorization for a plurality of dimension counts. An average inverse top dimension top term ranking for the plurality of documents is further calculated based on the SVD factorization for the plurality of dimension counts. A number of dimensions is determined based on the average top dimension weight and the average inverse top dimension top term ranking. A topic model is built for the plurality of documents based on the number of dimensions. The topic model is adapted to identify patterns of terms that correspond to semantic topics in at least the plurality of documents.

Dimension optimization in singular value decomposition-based topic models

Techniques are described for optimizing a number of dimensions for performing a singular value decomposition (SVD) factorization. Embodiments tokenize each of a plurality of documents into a respective set of terms. For each of a plurality of dimension counts, embodiments perform the SVD factorization to determine a respective plurality of dimensions, the respective plurality of dimensions corresponding to the dimension count, determine, for each of the plurality of documents, a respective set of dimension weights for each of the plurality of dimensions, calculate an average top dimension weight across the sets of dimension weights for the plurality of documents and calculate an average inverse top dimension top term ranking across the sets of dimension weights for the plurality of documents. An optimal number of dimensions is calculated, based on the average top dimension weight and the average inverse top dimension top term ranking.

A particular method includes receiving a conflict notice from a first airfield computing agent associated with a first airfield at a first aircraft computing agent associated with a first aircraft. The conflict notice indicates that the first aircraft is associated with a first conflict of the first airfield. The method also includes identifying, based on parameters associated with the first aircraft, one or more actions associated with the first aircraft to address the first conflict.

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O'Fallon, MO, United States of America

Stephen P Jewett