No, that's not my feedback: TV show recommendation using watchable interval
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Cho, Kyung-Jae | - |
dc.contributor.author | Lee, Yeon-Chang | - |
dc.contributor.author | Han, Kyungsik | - |
dc.contributor.author | Choi, Jaeho | - |
dc.contributor.author | Kim, Sang-Wook | - |
dc.date.accessioned | 2022-07-09T19:24:30Z | - |
dc.date.available | 2022-07-09T19:24:30Z | - |
dc.date.created | 2021-05-13 | - |
dc.date.issued | 2019-04 | - |
dc.identifier.issn | 1084-4627 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/hanyang/handle/2021.sw.hanyang/148004 | - |
dc.description.abstract | 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. | - |
dc.language | 영어 | - |
dc.language.iso | en | - |
dc.publisher | IEEE Computer Society | - |
dc.title | No, that's not my feedback: TV show recommendation using watchable interval | - |
dc.type | Article | - |
dc.contributor.affiliatedAuthor | Kim, Sang-Wook | - |
dc.identifier.doi | 10.1109/ICDE.2019.00036 | - |
dc.identifier.scopusid | 2-s2.0-85067924587 | - |
dc.identifier.wosid | 000477731600029 | - |
dc.identifier.bibliographicCitation | Proceedings - International Conference on Data Engineering, v.2019-April, pp.316 - 327 | - |
dc.relation.isPartOf | Proceedings - International Conference on Data Engineering | - |
dc.citation.title | Proceedings - International Conference on Data Engineering | - |
dc.citation.volume | 2019-April | - |
dc.citation.startPage | 316 | - |
dc.citation.endPage | 327 | - |
dc.type.rims | ART | - |
dc.type.docType | Conference Paper | - |
dc.description.journalClass | 1 | - |
dc.description.isOpenAccess | N | - |
dc.description.journalRegisteredClass | scopus | - |
dc.relation.journalResearchArea | Computer Science | - |
dc.relation.journalWebOfScienceCategory | Computer Science, Information Systems | - |
dc.subject.keywordPlus | Data processing | - |
dc.subject.keywordPlus | Recommender systems | - |
dc.subject.keywordPlus | Implicit feedback | - |
dc.subject.keywordPlus | Inherent characteristics | - |
dc.subject.keywordPlus | Novel concept | - |
dc.subject.keywordPlus | Prediction-based | - |
dc.subject.keywordPlus | State-of-the-art methods | - |
dc.subject.keywordPlus | TV channels | - |
dc.subject.keywordPlus | Watchable episode | - |
dc.subject.keywordPlus | Watchable interval | - |
dc.subject.keywordPlus | Collaborative filtering | - |
dc.subject.keywordAuthor | Implicit feedback | - |
dc.subject.keywordAuthor | Recommender systems | - |
dc.subject.keywordAuthor | Tv show recommendation | - |
dc.subject.keywordAuthor | Watchable episode | - |
dc.subject.keywordAuthor | Watchable interval | - |
dc.identifier.url | https://ieeexplore.ieee.org/document/8731575/ | - |
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