Kunyoung Kim, Jeongbin Lee, Mye Sohn, Journal of Internet Computing and Services, Vol. 24, No. 6, pp. 127-135, Dec. 2023
10.7472/jksii.2023.24.6.127, Full Text:  HTML
Keywords: Battlefield situation awareness, Decision Making, Natural Language Processing, Language Model, Collaborative Filtering, named entity recognition

Abstract

With the development of information and communication technology, the amount of information produced and shared in the battlefield and stored and managed in the system dramatically increased. This means that the amount of information which cansupport situational awareness and decision making of the commanders has increased, but on the other hand, it is also a factor that hinders rapid decision making by increasing the information overload on the commanders. To overcome this limitation, this study proposes a method to automatically search, select, and summarize documents that can help the commanders to understand the battlefield situation reports that he or she received. First, named entities are discovered from the battlefield situation report using a named entity recognition method. Second, the documents related to each named entity are discovered. Third, a language model and collaborative filtering are used to select the documents. At this time, the language model is used to calculate the similarity between the received report and the discovered documents, and collaborative filtering is used to reflect the commander's document reading history. Finally, sentences containing each named entity are selected from the documents and sorted. The experiment was carried out using academic papers since their characteristics are similar to military documents, and the validity of the proposed method was verified.

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