Sentiment-Topic Modelling in Text Mining

Autoria(s): Lin, Chenghua; Ibeke, Emmanuel Ebuka; Wyner, Adam Zachary; Guerin, Frank
Contribuinte(s)

University of Aberdeen, Natural & Computing Sciences, Computing Science

University of Aberdeen, Natural & Computing Sciences

University of Aberdeen, Energy
Data(s)

05/08/2016

05/08/2016

01/09/2015

20/09/2001
Resumo

Peer reviewed

Postprint
Formato

9
Identificador

Lin , C , Ibeke , E E , Wyner , A Z & Guerin , F 2015 , ' Sentiment-Topic Modelling in Text Mining ' Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery , vol 5 , no. 5 , pp. 246-254 . , 10.1002/widm.1161

1942-4795

PURE: 53925165

PURE UUID: 8bd8081c-c591-4e77-882e-2425e07c53de

http://hdl.handle.net/2164/6699

http://dx.doi.org/10.1002/widm.1161
Idioma(s)

eng
Relação

Wiley Interdisciplinary Reviews: Data Mining and Knowledge Discovery
Direitos

This is the peer reviewed version of the following article: Lin, C., Ibeke, E., Wyner, A. and Guerin, F. (2015), Sentiment–topic modeling in text mining. WIREs Data Mining Knowl Discov, 5: 246–254. which has been published in final form at doi: 10.1002/widm.1161. This article may be used for non-commercial purposes in accordance with Wiley Terms and Conditions for Self-Archiving.
Palavras-Chave #QA75 Electronic computers. Computer science #QA75
Tipo

Journal article
Acesso ao item digital