No, that's not my feedback: TV show recommendation using watchable interval

  • Cho, Kyung-Jae; 
  • Lee, Yeon-Chang; 
  • Han, Kyungsik; 
  • Choi, Jaeho; 
  • Kim, Sang-Wook
Citations

WEB OF SCIENCE

18
Citations

SCOPUS

20

초록

As the number of TV channels increases, it is becoming important to recommend TV shows that users prefer to watch. To this end, we investigate the inherent characteristics of implicit feedback given in the TV show domain, and identify the challenges for building an effective TV show recommendation. Based on the unique characteristics, we define a user's watchable interval, the most important and novel concept in understanding users' true preferences. In order to reflect this new concept into the TV show recommendation, we propose a novel framework based on collaborative filtering. Our framework is composed of (1) preference estimation based on a user's watchable interval, (2) preference prediction based on confidence exploiting watch able episodes, and (3) top-N recommendation considering TV show's staying and remaining times. Using a real-world TV show dataset, we demonstrate that our framework effectively solves the challenges and significantly outperforms other existing state-of-the-art methods.

키워드

Implicit feedback; Recommender systems; Tv show recommendation; Watchable episode; Watchable interval; Data processing; Recommender systems; Implicit feedback; Inherent characteristics; Novel concept; Prediction-based; State-of-the-art methods; TV channels; Watchable episode; Watchable interval; Collaborative filtering
제목
No, that's not my feedback: TV show recommendation using watchable interval
저자
Cho, Kyung-Jae; Lee, Yeon-Chang; Han, Kyungsik; Choi, Jaeho; Kim, Sang-Wook
DOI
10.1109/ICDE.2019.00036
발행일
2019-04
유형
Conference Paper
저널명
Proceedings - International Conference on Data Engineering
권
2019-April
페이지
316 ~ 327