01674nas a2200277   4500000000100000000000100001008004100002260000900043653001700052653002100069653000800090653003100098653002000129653001400149653001200163100001900175700002100194700001400215700001900229700001800248700001900266245009700285300001200382490000700394520099500401       2020                            d  c202010adata science10amachine learning10aNLP10asemantic similarity search10atext similarity10athesaurus10atriples1 aGiavid Valiyev1 aMarcello Piraino1 aArvid Kok1 aMichael Street1 aIvana Mestric1 aRetzius Birger00aInitial Exploitation of Natural Language Processing Techniques on NATO Strategy and Policies  a187-2020 v473 a<p>This paper describes initial exploitation of Natural Language Processing (NLP) techniques applied to a specific set of related NATO documents. In particular, the text similarity technique was applied to document sets with the aim of capturing the relationships between documents or sections of documents from semantic and syntactic perspectives. Thesaurus and triple extraction techniques allowed the understanding of the sentences beyond the syntactic structure, thus improving the accuracy in capturing similar content across documents with diverse syntactic structures. The objective is to assess whether Natural Language Processing tools can retrieve relationships and gaps between such kinds of textual data. This work improves interoperability in NATO by enhancing the development and application of policies, directives and other documents, which dictate how Consultation, Command and Control (C3) systems across the Alliance interoperate and support NATO's operational needs.</p>