인문학
사회과학
자연과학
공학
의약학
농수해양학
예술체육학
복합학
지원사업
학술연구/단체지원/교육 등 연구자 활동을 지속하도록 DBpia가 지원하고 있어요.
커뮤니티
연구자들이 자신의 연구와 전문성을 널리 알리고, 새로운 협력의 기회를 만들 수 있는 네트워킹 공간이에요.
논문 기본 정보
- 저자정보
초록·키워드
With the widespread application of information technology, smart tourism has emerged as an important direction for the development of the tourism industry. To improve the technological level of the smart tourism industry, a technology based on optimized Apriori association rule mining algorithm is designed. The Spark in-memory computing framework is chosen as the distributed programming framework to store elastic distributed datasets in distributed memory. The support is used to measure the probability of two scenic spots appearing simultaneously, and the order of tourists visiting the scenic spots is considered. A complete data mining process is designed. In the test of the association rules, the research method generated 4,271 association rules at a confidence level of 0.056. When the minimum support threshold of the research method was 30%, the number of invalid frequent itemsets generated was only 831. In the analysis of operational accuracy, the research method maintained an accuracy of over 98.8% when analyzing a data volume of 10,000. This indicates that the research method has good data mining performance and faster computation speed during runtime. The research method can provide good technical support for smart tourism.
본문·목차
인공지능 문자 인식 모델을 통해 추출된 텍스트로, 일부 오타나 오류가 포함될 수 있으나 지속적으로 개선 중입니다.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
오류를 발견하셨다면 해당 부분을 드래그한 후 ' 를 통해 신고해주세요.
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UCI(KEPA) : I410-151-26-02-095621715