The aim of this study is to evaluate the discovery of temporal themes in a text stream. The authors evaluate a probabilistic model for unsupervised learning to solve the problem and a scheme for theme evolution visualisation is proposed. The proposed methods will be evaluated on a collection of Bayesian Analysis abstracts (www.bayesian.org). The output will be a temporal summary of Bayesian related research themes and how they evolve over time, captured in a graph
Reference:
De Waal A. 2006. Evolution of bayesian-related research over time: a temporal text mining task. ISBA 8th world meeting on Bayesian statistics, Valencia 2006, pp 17
de Waal, A. (2006). Evolution of bayesian-related research over time: a temporal text mining task. Oxford University Press. http://hdl.handle.net/10204/2818
de Waal, A. "Evolution of bayesian-related research over time: a temporal text mining task." (2006): http://hdl.handle.net/10204/2818
de Waal A, Evolution of bayesian-related research over time: a temporal text mining task; Oxford University Press; 2006. http://hdl.handle.net/10204/2818 .
Edited by the Conference Programme Committee, Bayesian Statistics 8, the Valencia 8 conference proceedings, have beeen published in September 2007 by Oxford University Press
