The Boeing Company

Rodney Allen Tjoelker

Anne Kao

Changzhou Wang

Jai Joon Choi

Stephen Robert Poteet

William R Ferng

Sabyasachi Basu

Shuguang Song

Ranjan Kumar Paul

William R Frans

John B Maggiore

Lesley H Quach

Roman D Fresnedo

Valeria V Thompson

Virginia L Wheway

A method including processing social network data to establish a tensor model of the social network data, the tensor model having at least an order of four. The tensor model is decomposed into a plurality of principal factors. A summary tensor is synthesized from a subset of the plurality of principal factors. The summary tensor represents a plurality of relationships among a plurality of entities in the tensor model. A synthesis of relationships is formed and stored. At least one parameter is identified using one of the summary tensor and a single principal factor in the subset. The at least one parameter is selected from the group consisting of: a correlation among the plurality of entities, a similarity between two of the plurality of entities, and a time-based trend of changes in the synthesis of relationships. The at least one parameter is communicated.

Determination of latent interactions in social networks

A method of mining data to discover activity patterns within the data is described. The method includes receiving data to be mined from at least one data source, determining which of a number of specified interests and constraints are associated with the mining process, selecting corresponding mining agents that combine search algorithms with propagators from the specified constraints, and finding any activity patterns that meet the specified interests and constraints.

Methods and framework for constraint-based activity mining (CMAP)

A system, method, and computer program product for predicting failure of a vehicle system or subsystem by using statistical analysis of prior maintenance messages and vehicle failures, such that the predictions of failures may be incorporated into a vehicle monitoring and reporting system. Maintenance message data and vehicle system or subsystem failure data are collected from a central maintenance computer of a vehicle, such as an aircraft. This maintenance message and vehicle system or subsystem failure data are analyzed to discern relationships between maintenance messages and vehicle system or subsystem failures which will enable future failures to be predicted. By predicting future failures, maintenance can be performed in time to prevent the vehicle failure and thereby avoid unnecessary costs and unscheduled interruptions of vehicle operations.

System, method, and computer program product for fault prediction in vehicle monitoring and reporting system

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Bellevue, WA, United States of America

Rodney Allen Tjoelker