User timeline and interest-based collaborative filtering on social network
DC Field | Value | Language |
---|---|---|
dc.contributor.author | Pham, X.H. | - |
dc.contributor.author | Jung, J.J. | - |
dc.contributor.author | Nam, B.K.H. | - |
dc.contributor.author | Nguyen, T.T. | - |
dc.date.accessioned | 2021-08-17T02:40:10Z | - |
dc.date.available | 2021-08-17T02:40:10Z | - |
dc.date.issued | 2016-11 | - |
dc.identifier.issn | 1867-8211 | - |
dc.identifier.uri | https://scholarworks.bwise.kr/cau/handle/2019.sw.cau/48433 | - |
dc.description.abstract | A lot of users and large amount of information have been posted and shared through on-line systems. User timeline and interest are important features on recommendation systems (e.g., user likes watching action movies in the morning, and likes watching drama movies in the afternoon however he/she likes watching thriller movies in the evening) and also on social network. There are some recommendation applications have been developed on social network to support users selecting what kind of wanted items based on user timeline and interest. However, there is not any approaches based on user timeline and interest have been proposed that user interest have been separated into partitions of user interest. Thus, a recommendation mechanism will be applied on social networks based on extracting user timeline and user interest that is necessary. In this paper, we propose a new approach that user interest will be determined on a set of time partitions. | - |
dc.format.extent | 9 | - |
dc.language | 영어 | - |
dc.language.iso | ENG | - |
dc.publisher | Springer Verlag | - |
dc.title | User timeline and interest-based collaborative filtering on social network | - |
dc.type | Article | - |
dc.identifier.doi | 10.1007/978-3-319-29236-6_14 | - |
dc.identifier.bibliographicCitation | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST, v.165, pp 132 - 140 | - |
dc.description.isOpenAccess | N | - |
dc.identifier.scopusid | 2-s2.0-84964067913 | - |
dc.citation.endPage | 140 | - |
dc.citation.startPage | 132 | - |
dc.citation.title | Lecture Notes of the Institute for Computer Sciences, Social-Informatics and Telecommunications Engineering, LNICST | - |
dc.citation.volume | 165 | - |
dc.type.docType | Conference Paper | - |
dc.publisher.location | 독일 | - |
dc.subject.keywordAuthor | Context | - |
dc.subject.keywordAuthor | Recommendation systems | - |
dc.subject.keywordAuthor | User interest | - |
dc.subject.keywordAuthor | User timeline | - |
dc.subject.keywordPlus | Motion pictures | - |
dc.subject.keywordPlus | Recommender systems | - |
dc.subject.keywordPlus | User interfaces | - |
dc.subject.keywordPlus | Action movies | - |
dc.subject.keywordPlus | Context | - |
dc.subject.keywordPlus | Important features | - |
dc.subject.keywordPlus | Large amounts | - |
dc.subject.keywordPlus | New approaches | - |
dc.subject.keywordPlus | Recommendation mechanism | - |
dc.subject.keywordPlus | User interests | - |
dc.subject.keywordPlus | User timeline | - |
dc.subject.keywordPlus | Collaborative filtering | - |
dc.description.journalRegisteredClass | scopus | - |
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