| Title |
Convolutional Neural Network based Filtering-Scoring System for Rating Prediction of Travel Attractions using Social Media |
| Authors |
김민구(Mingu Kim) ; 홍승우(Seungwoo Hong) ; 서일홍(Il Hong Suh) |
| DOI |
https://doi.org/10.5573/ieie.2019.56.9.43 |
| Keywords |
자연어 처리, 감성 분석, 소셜미디어, 여행지 평점, Convolutional Neural Network |
| Abstract |
Rating information of travel attractions provides intuitive and comprehensive information for trip planning. However, such rating information has a disadvantage that it is difficult to guarantee high reliability when there are only a few reviews. Therefore, in this paper, we propose a system for predicting the ratings of tourist attractions using posts from social media services. The system searches and collects a large number of posts from a social media by using the name of a given tourist attraction as a keyword, classifies the posts into a reviews and non-rieviews using a filtering model, predicts the rating of each review using a scoring model. Predicted ratings are then averaged to predict the overall rating of the given travel attraction. Also, deep learning based filtering and scoring model structures are proposed along with the Korean data argumentation method to improve the performance of the proposed system. |