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A Twofold-LDA Model for Customer Review Analysis

Burns, Nicola, Bi, Yaxin, Wang, Hui and Anderson, Terry (2011) A Twofold-LDA Model for Customer Review Analysis. In: 2011 IEEE/WIC/ACM International Conferences on Web Intelligence and Intelligent Agent Technology. IEEE Press. Vol 1 4 pp. [Conference contribution]

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DOI: 10.1109/WI-IAT.2011.73


The Latent Dirichlet Allocation model is an unsupervised generative model that is widely used for topic modelling in text. We propose to add supervision to the model in the form of domain knowledge to direct the focus of topics to more relevant aspects than the topics produced by standard LDA. Experimental results demonstrate the effectiveness of our method. We also propose a novel Twofold-LDA model to improve the current output of LDA in order to visualize results in graphical form, which can ultimately be used by potential customers. Experiments show the benefit of this new output, with the ability to produce topics focused on our desired aspects in a user friendly chart.

Item Type:Conference contribution (Paper)
Faculties and Schools:Faculty of Computing & Engineering
Faculty of Computing & Engineering > School of Computing and Mathematics
Research Institutes and Groups:Computer Science Research Institute
Computer Science Research Institute > Artificial Intelligence and Applications
ID Code:25484
Deposited By: Dr Yaxin Bi
Deposited On:19 Feb 2014 13:37
Last Modified:19 Feb 2014 13:37

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