Text mining and natural language processing for the early stages of space mission design

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Abstract

A considerable amount of data related to space mission design has been accumulatedsince artificial satellites started to venture into space in the 1950s. This data has todaybecome an overwhelming volume of information, triggering a significant knowledgereuse bottleneck at the early stages of space mission design. Meanwhile, virtual assistants,text mining and Natural Language Processing techniques have become pervasiveto our daily life.The work presented in this thesis is one of the first attempts to bridge the gapbetween the worlds of space systems engineering and text mining. Several novel modelsare thus developed and implemented here, targeting the structuring of accumulateddata through an ontology, but also tasks commonly performed by systems engineerssuch as requirement management and heritage analysis. A first collection of documentsrelated to space systems is gathered for the training of these methods. Eventually, thiswork aims to pave the way towards the development of a Design Engineering Assistant(DEA) for the early stages of space mission design. It is also hoped that this work willactively contribute to the integration of text mining and Natural Language Processingmethods in the field of space mission design, enhancing current design processes.

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