Please use this identifier to cite or link to this item: http://hdl.handle.net/2445/109443
Title: A tensor based approach for temporal topic modeling
Author: Julià Carrillo, Oriol
Director: Vitrià i Marca, Jordi
Keywords: Tractament del llenguatge natural (Informàtica)
Tesis
Aprenentatge automàtic
Probabilitats
Algorismes computacionals
Natural language processing (Computer science)
Theses
Machine learning
Probabilities
Computer algorithms
Issue Date: 26-Jun-2016
Abstract: Latent Dirichlet Allocation (LDA) are a suite of algorithms that are often used for topic modeling. We study the statistical model behind LDA and review how tensor methods can be used for learning LDA, as well as implement a variation of an already existing method. Next, we present an innovative algorithm for temporal topic modeling and provide a new dataset for learning topic models over time. Last, we create a visualization for the word-topic probabilities.
Note: Treballs Finals de Grau de Matemàtiques, Facultat de Matemàtiques, Universitat de Barcelona, Any: 2016, Director: Jordi Vitrià i Marca
URI: http://hdl.handle.net/2445/109443
Appears in Collections:Treballs Finals de Grau (TFG) - Matemàtiques

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