한국인터넷정보학회 논문지
Current Result Document :
| 한글제목(Korean Title) |
A Study of Recommendation Systems for Supporting Command and Control (C2) Workflow |
| 영문제목(English Title) |
A Study of Recommendation Systems for Supporting Command and Control (C2) Workflow |
| 저자(Author) |
Gyudong Park
Gi-Yoon Jeon
Mye Sohn
Jongmo Kim
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| 원문수록처(Citation) |
VOL 23 NO. 01 PP. 0125 ~ 0134 (2022. 02) |
한글내용
(Korean Abstract) |
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영문내용
(English Abstract) |
The development of information communication and artificial intelligence technology requires the intelligent command and control (C2) system for Korean military, and various studies are attempted to achieve it. In particular, as a volume ofinformation in the C2 workflow increases exponentially, this study pays attention to the collaborative filtering (CF) and recommendation systems (RS) that can provide the essential information for the users of the C2 system has been developed. The RS performing information filtering in the C2 system should provide an explanatory recommendation and consider the context of the tasks and users. In this paper, we propose a contextual pre-filtering CARS framework that recommends information in the C2 workflow. The proposed framework consists of four components: 1) contextual pre-filtering that filters data in advance based on the context and relationship of the users, 2) feature selection to overcome the data sparseness that is a weak point for the CF, 3) the proposed CF with the features distances between the users used to calculate user similarity, and 4) rule-based post filtering to reflect user preferences. In order to evaluate the superiority of this study, various distance methods of the existing CF method were compared to the proposed framework with two experimental datasets in real-world. As a result of comparative experiments, it was shown that the proposed framework was superior in terms of MAE, MSE, and MSLE. |
| 키워드(Keyword) |
Command and Control(C2) system
Feature selection
Collaborative Filtering
Context-aware Recommendation System
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| 파일첨부 |
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