Aptima, Inc.

Robert McCormack

Andrew P Duchon

Paul David Allopenna

John Colonna-Romano

Kari Kelton

Pacey Foster

Kara Orvis

Emily K M Stelzer

William J Salter

Kathryn Engel

Shawn Weil

Amy Alexander Horrey

David Kramer

Jamie L Estock

The present invention relate to a method and system to predict the likelihood of data topics that may occur from data sources. The likelihood of the data topics may be predicted over other dimensions of time or over other dimensions. In the present invention, a topic means a defining characteristic, usually represented as a data element, of a single feature, activity, subject, behavior, event or an aggregation of such defining characteristics.

Method and system to predict the likelihood of topics

Embodiments of the disclosed systems and methods establish quantitative relationships between system features and system objectives. In some embodiments, the features have a plurality of feature values related to the objective and the methods comprise analyzing a mathematical functional relationship between the plurality of feature values and the objective to create a plurality of objective values reflecting the ability of the feature values to satisfy the objective, selecting a feature value and analyzing the relationship to create an objective value; and generating an objective measure reflecting the objective value. In some embodiments, the mathematical function comprises a polynomial interpolation. In some embodiments, the features are a fidelity dimension and the feature values are values of fidelity in a processor based aircraft simulator.

System and method for comparing system features

The present invention relates in general to methods and systems for comparing and maximizing the optimal selection of a first set of one or more data objects to a set of second data objects. In one embodiment, the first set of data objects represent one or more tasks to be fulfilled by a set of capabilities represented by the second data objects. In one embodiment, methods and systems are provided that apply topic modeling and similarity metrics to determine the optimal selection. In one embodiment, methods and systems are provided to determine the appropriateness of a set of second data objects to satisfy the requirements of a first data object given interaction attributes. Embodiments may be used to compare mission requirements with potential team members to determine the appropriateness of team members and teams for a given mission based on interaction attributes of the team members and teams.

Method and system to compare data objects

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Somerville, MA, United States of America

Robert McCormack