OLLDA: Dynamic and Scalable Topic Modelling for Twitter : AN ONLINE SUPERVISED LATENT DIRICHLET ALLOCATION ALGORITHM

OLLDA: Dynamic and Scalable Topic Modelling for Twitter : AN ONLINE SUPERVISED LATENT DIRICHLET ALLOCATION ALGORITHM

Providing high quality of topics inference in today's large and dynamic corpora, such as Twitter, is a challenging task. This is especially challenging taking into account that the content in this environment contains short texts and many abbreviations. This project proposes an improvement of a...

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Bibliographic Details
Main Author:	Jaradat, Shatha
Format:	Others
Language:	English
Published:	KTH, Skolan för informations- och kommunikationsteknik (ICT) 2015
Subjects:	Latent Dirichlet Allocation Labeled Latent Dirichlet Allocation online Variational Bayes for LDA multi-labeled supervised Twitter recommendations variational inference. Computer and Information Sciences Data- och informationsvetenskap
Online Access:	http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-177535

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