Sentence Recommendation Using Beam Search in a Military Intelligent Image Analysis System


KIPS Transactions on Software and Data Engineering, Vol. 10, No. 11, pp. 521-528, Nov. 2021
https://doi.org/10.3745/KTSDE.2021.10.11.521,   PDF Download:
Keywords: NLP, Beam Search, Military, Seq2seq, Attention Mechanism
Abstract

Existing image analysis systems in use in the military field are carried out by readers analyzing and identifying images themselves, writing and disseminating related content, and in this process, repetitive tasks are frequent, resulting in workload. In this paper, to solve the previous problem, we proposed an algorithm that can operate the Seq2Seq model on a word basis, which operates on a sentence basis, and applied the Attention technique to improve accuracy. In addition, by applying the Beam Search technique, we would like to recommend various current identification sentences based on the past identification contents of a specific area. It was confirmed through experiments that the Beam Search technique recommends sentences more effectively than the existing greedy Search technique, and confirmed that the accuracy of recommendation increases when the size of Beam is large.


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Cite this article
[IEEE Style]
H. Na, T. Jeon, H. Kang, J. Ahn, D. Im, "Sentence Recommendation Using Beam Search in a Military Intelligent Image Analysis System," KIPS Transactions on Software and Data Engineering, vol. 10, no. 11, pp. 521-528, 2021. DOI: https://doi.org/10.3745/KTSDE.2021.10.11.521.

[ACM Style]
Hyung-Sun Na, Tae-Hyeon Jeon, Hyung-Seok Kang, Jinhyun Ahn, and Dong-Hyuk Im. 2021. Sentence Recommendation Using Beam Search in a Military Intelligent Image Analysis System. KIPS Transactions on Software and Data Engineering, 10, 11, (2021), 521-528. DOI: https://doi.org/10.3745/KTSDE.2021.10.11.521.