A study on the Extraction of Similar Information using Knowledge Base Embedding for Battlefield Awareness (전장상황인식을 위한 지식베이스 임베딩 기반 유사 단어 추출에 관한 연구)

Sang-Min Kim (김상민); So-yeon Jin (진소연); Woo-sin Lee (이우신)

doi:10.9708/jksci.2021.26.11.033

A study on the Extraction of Similar Information using Knowledge Base Embedding for Battlefield Awareness

Journal of The Korea Society of Computer and Information
Abbr : JKSCI
2021, 26(11), pp.33-40
DOI : 10.9708/jksci.2021.26.11.033
Publisher : The Korean Society Of Computer And Information
Research Area : Engineering > Computer Science
Received : October 21, 2021
Accepted : November 24, 2021
Published : November 30, 2021

Sang-Min Kim ¹, So-yeon Jin ², Woo-sin Lee ²

¹한화시스템
²한화 시스템

Accredited

ABSTRACT

Due to advanced complex strategies, the complexity of information that a commander must analyze is increasing. An intelligent service that can analyze battlefield is needed for the commander's timely judgment. This service consists of extracting knowledge from battlefield information, building a knowledge base, and analyzing the battlefield information from the knowledge base. This paper extract information similar to an input query by embedding the knowledge base built in the 2nd step. The transformation model is needed to generate the embedded knowledge base and uses the random-walk algorithm. The transformed information is embedding using Word2Vec, and Similar information is extracted through cosine similarity. In this paper, 980 sentences are generated from the open knowledge base and embedded as a 100-dimensional vector and it was confirmed that similar entities were extracted through cosine similarity.

KEYWORDS

Knowledge Base, Embedding, Battlefield Awareness, Natural Language Processing, Artificial Intelligence

Citation status

* References for papers published after 2023 are currently being built.

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Journal Central

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A study on the Extraction of Similar Information using Knowledge Base Embedding for Battlefield Awareness

ABSTRACT

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Citation status

* References for papers published after 2023 are currently being built.

Journal of The Korea Society of Computer and Information 2023 KCI Impact Factor : 0.65

A study on the Extraction of Similar Information using Knowledge Base Embedding for Battlefield Awareness

ABSTRACT

KEYWORDS

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* References for papers published after 2023 are currently being built.