Please use this identifier to cite or link to this item: http://scholarbank.nus.edu.sg/handle/10635/128459
Title: LDA-based industry classification
Authors: Fang, F.
Dutta, K. 
Datta, A. 
Keywords: Industry classification
LDA
Peers identification
Text mining
Issue Date: 2013
Citation: Fang, F.,Dutta, K.,Datta, A. (2013). LDA-based industry classification. International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design 3 : 2500-2509. ScholarBank@NUS Repository.
Abstract: Industry classification is a crucial step for financial analysis. However, existing industry classification schemes have several limitations. In order to overcome these limitations, in this paper, we propose an industry classification methodology on the basis of business commonalities using the topic features learned by the Latent Dirichlet Allocation (LDA) from firms' business descriptions. Two types of classification - firmcentric classification and industry-centric classification were explored. Preliminary evaluation results showed the effectiveness of our method. © (2013) by the AIS/ICIS Administrative Office. All rights reserved.
Source Title: International Conference on Information Systems (ICIS 2013): Reshaping Society Through Information Systems Design
URI: http://scholarbank.nus.edu.sg/handle/10635/128459
ISBN: 9781629934266
Appears in Collections:Staff Publications

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