A Social Travel Recommendation System using Item-based collaborative filtering
- Authors
- 김대호; 송제인; 유소엽; 정옥란
- Issue Date
- 2018
- Publisher
- 한국인터넷정보학회
- Keywords
- Personalized Recommendation; Item-based Collaborative Filtering; Apache Mahout; Social Travel Trends; Intimacy
- Citation
- 인터넷정보학회논문지, v.19, no.3, pp.7 - 14
- Journal Title
- 인터넷정보학회논문지
- Volume
- 19
- Number
- 3
- Start Page
- 7
- End Page
- 14
- URI
- https://scholarworks.bwise.kr/gachon/handle/2020.sw.gachon/4996
- DOI
- 10.7472/jksii.2018.19.3.7
- ISSN
- 1598-0170
- Abstract
- As SNS(Social Network Service) becomes a part of our life, new information can be derived through various information provided by SNS. Through the public timeline analysis of SNS, we can extract the latest tour trends for the public and the intimacy through the social relationship analysis in the SNS. The extracted intimacy can also be used to make the personalized recommendation by adding the weights to friends with high intimacy. We apply SNS elements such as analyzed latest trends and intimacy to item-based collaborative filtering techniques to achieve better accuracy and satisfaction than existing travel recommendation services in a new way. In this paper, we propose a social travel recommendation system using item - based collaborative filtering.
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Collections - IT융합대학 > 소프트웨어학과 > 1. Journal Articles
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