Decentralized Topic Modelling with Latent Dirichlet Allocation

Concept Discovery and Automatic Semantic Annotation for Language Understanding in an Information-Query Dialogue System Using Latent Dirichlet Allocation and Segmental

In this paper we have presented a new smoothed topic model using hierarchical Pitman-Yor process priors and applied it to prediction of chord sequences and to chord-based musical

Spatio-temporal Analysis of Dynamic Origin-Destination Data Using Latent Dirichlet Allocation: Application to Vélib’ Bike Sharing System of Paris.4. data using Latent

By shifting the data domain from text to each coun- try’s export flow of each product, we managed to develop a typology of global trade based on a number of latent components..

Training topic models As in (Louis and Webber, 2014), we use Latent Dirichlet Allocation (LDA) (Blei et al., 2003) to train topic models on our monolingual biography data, taking

Pattern 1 showed slight dilution of medium chloride concentration, slight increase in sulfate concentration, a peak in DOC concen- tration on the day of the event, and clear dilution

Abstract: Worldwide schistosomiasis remains a serious public health problem with approximately 67 million people infected and 200 million at risk of infection from inhabiting

To make the model tractable we also introduced a matching graph clustered using connected component clustering, that can be used to quickly organize very large image collections,