Design of Good Bibimbap Restaurant Recommendation System Using TCA based on BigData
Suk-jin Kim, Yongsung Kim · Advanced Science and Technology Letters · 2014
This paper designs the model of bibimbap restaurant recommending 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.