Temporal analysis of text data using latent variable models
|Conference paper (help)|
|Temporal analysis of text data using latent variable models|
|Authors:||Lasse L. Mølgaard, Jan Larsen (DTU Compute), Cyril Goutte|
|Citation:||Machine Learning for Signal Processing, 2009. MLSP 2009. IEEE International Workshop on : 1-6. 2009|
|Meeting:||IEEE International Workshop on Machine Learning for Signal Processing, 2009|
|Database(s):||Google Scholar cites|
|Web:||DuckDuckGo Bing Google Yahoo! — Google PDF|
|Article:||Google Scholar PubMed|
|Restricted:||DTU Digital Library|
Temporal analysis of text data using latent variable models describes temporal text mining with stepwise probabilistic latent semantic analysis and global multiway PLSA.
Texts from Wikipedia was used to test the algorithm. Pages assigned to categories "Baroque composers" and "American composers" were used producing a corpus consisting of 7358 documents. 18536 terms were identified. Composers birthday were used as a third dimension.