원문정보
보안공학연구지원센터(IJSEIA)
International Journal of Software Engineering and Its Applications
Vol.8 No.7
2014.07
pp.95-106
피인용수 : 0건 (자료제공 : 네이버학술정보)
초록
영어
This paper designs the model of bibimbap restaurant recommendation system in BigData(collected from Twitter's data related to bibimbap). We suggests a TCA (Termite Colony Algorithm) k-means algorithm for clustering BigData, TCA algorithm that used the habits of termites. Through the TCA, finding the appropriate initial clustering needed for the K-means clusters is the goal. We recommend good Bibimpop restaurant to user, using "Bibimbap Restaurant database of Korea (2012)" and an "Taste Adjective Dictionary for the Globalization of Korean Food" for Ranking Algorithm.
목차
Abstract
1. Introduction
2. Related Work
2.1. BigData
2.2. Recommendation System
2.3. Clustering
3. Design for a Good Bibimbap Restaurant Recommendation System
3.1. Behavioral Habits of Termites
3.2. Termite Colony Algorithm
3.3. Similar Twitter Search Algorithm
3.4. Ranking and Recommendation
4. Conclusions
References
1. Introduction
2. Related Work
2.1. BigData
2.2. Recommendation System
2.3. Clustering
3. Design for a Good Bibimbap Restaurant Recommendation System
3.1. Behavioral Habits of Termites
3.2. Termite Colony Algorithm
3.3. Similar Twitter Search Algorithm
3.4. Ranking and Recommendation
4. Conclusions
References
저자정보
참고문헌
자료제공 : 네이버학술정보