Multi-model or single-model?: A study of movie box-office revenue prediction
DC Field | Value | Language |
---|---|---|
dc.contributor.author | He, G. | - |
dc.contributor.author | Lee, S. | - |
dc.date.available | 2019-04-10T10:16:44Z | - |
dc.date.created | 2018-04-17 | - |
dc.date.issued | 2015 | - |
dc.identifier.isbn | 9781509001545 | - |
dc.identifier.uri | http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/32689 | - |
dc.description.abstract | Although many studies tried to predict movie revenues in the last decade, the performance and conclusions are conflictive because different data is used. Some studies report that using social data like reviews can obtain the better prediction than using only metadata of movies, but we demonstrate metadata can beat social data in some cases. In this paper, we utilize EM (Expectation Maximization) algorithm to divide movies into several groups, and then for each group we learn one model to predict movie box-office revenue separately. Experimental results show that using multiple models (Multimodel) can obtain more accurate prediction than using a single model (Single-model). © 2015 IEEE. | - |
dc.publisher | Institute of Electrical and Electronics Engineers Inc. | - |
dc.relation.isPartOf | Proceedings of CIT 2015, IUCC 2015, DASC 2015 and PICom 2015 | - |
dc.title | Multi-model or single-model?: A study of movie box-office revenue prediction | - |
dc.type | Conference | - |
dc.identifier.doi | 10.1109/CIT/IUCC/DASC/PICOM.2015.46 | - |
dc.type.rims | CONF | - |
dc.identifier.bibliographicCitation | CIT 2015, IUCC 2015, DASC 2015 and PICom 2015, pp.321 - 325 | - |
dc.description.journalClass | 2 | - |
dc.identifier.scopusid | 2-s2.0-84964220644 | - |
dc.citation.conferenceDate | 2015-10-26 | - |
dc.citation.endPage | 325 | - |
dc.citation.startPage | 321 | - |
dc.citation.title | CIT 2015, IUCC 2015, DASC 2015 and PICom 2015 | - |
dc.contributor.affiliatedAuthor | Lee, S. | - |
dc.type.docType | Conference Paper | - |
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