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텍스트 마이닝을 활용한 산림 공공애플리케이션의 보완 및 개선 연구
- 성준경;
- 박윤서;
- 윤화영;
- 양봉숙;
- 강규영
초록
As forest disasters such as forest fires and landslides increase due to climate change, and social demand for forest recreation and welfare services increases, the Korea Forest Service provides forest disaster warning and prevention (Smart Forest Disaster) and forest recreation and welfare (Forest Outing e) services through mobile applications. This study identified problems and suggested improvement and development plans through text mining analysis of user evaluations and reviews of these public applications. The target data of the analysis were 454 cases (49 cases of "Smart Forest Disaster" and 405 cases of "Forest Outing e") imported from two major app stores (Google Play Store and Apple App Store), and TF-IDF and sentiment analysis were performed on them. As a result, it was found that the 'Smart Forest Disaster' app needed to supplement the reporting function, and 'Forest Outing e' needed overall improvement to increase system stability and reliability.
키워드
- 제목
- 텍스트 마이닝을 활용한 산림 공공애플리케이션의 보완 및 개선 연구
- 제목 (타언어)
- A Study on the Supplementation and Improvement of Forest Public Applications Using Text Mining Analysis
- 저자
- 성준경; 박윤서; 윤화영; 양봉숙; 강규영
- 발행일
- 2024-10
- 저널명
- Crisisonomy
- 권
- 20
- 호
- 10
- 페이지
- 15 ~ 27