원문정보
Personalized Book Curation System based on Integrated Mining of Book Details and Body Texts
초록
영어
The content curation service through big data analysis is receiving great attention in various content fields, such as film, game, music, and book. This service recommends personalized contents to the corresponding user based on user's preferences. The existing book curation systems recommended books to users by using bibliographic citation, user profile or user log data. However, these systems are difficult to recommend books related to character names or spatio-temporal information in text contents. Therefore, in this paper, we suggest a personalized book curation system based on integrated mining of a book. The proposed system consists of mining system, recommendation system, and visualization system. The mining system analyzes book text, user information or profile, and SNS data. The recommendation system recommends personalized books for users based on the analysed data in the mining system. This system can recommend related books using based on book keywords even if there is no user information like new customer. The visualization system visualizes book bibliographic information, mining data such as keyword, characters, character relations, and book recommendation results. In addition, this paper also includes the design and implementation of the proposed mining and recommendation module in the system. The proposed system is expected to broaden users' selection of books and encourage balanced consumption of book contents.
목차
1. 서론
2. 관련 연구
2.1 콘텐츠 큐레이션 서비스 특징과 현황
2.2 도서 추천 큐레이션 서비스
3. 사용자 맞춤형 도서 추천 큐레이션시스템
3.1 마이닝 시스템(Mining System)
3.2 추천 시스템(Recommendation System)
3.3 시각화 시스템(Visualization System)
4. 시스템 설계 및 구현
4.1 인물 간 연관관계 추출 모듈
4.2 본문 및 독자 행동 기반 추천 모듈
5. 결론
References