Results 81 to 90 of about 3,030,763 (202)

topicmodels: An R Package for Fitting Topic Models [PDF]

, 2011
Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent ...
Kurt Hornik, Hornik, Kurt, Grün, Bettina, Bettina Grun   +3 more
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Unsupervised learning and natural language processing highlight research trends in a superbug

Frontiers in Artificial Intelligence
IntroductionAntibiotic-resistant Acinetobacter baumannii is a very important nosocomial pathogen worldwide. Thousands of studies have been conducted about this pathogen. However, there has not been any attempt to use all this information to highlight the
Carlos-Francisco Méndez-Cruz, Joel Rodríguez-Herrera, Alfredo Varela-Vega, Valeria Mateo-Estrada, Santiago Castillo-Ramírez   +4 more
doaj   +1 more source

Secure latent Dirichlet allocation

Frontiers in Digital Health
Topic modelling refers to a popular set of techniques used to discover hidden topics that occur in a collection of documents. These topics can, for example, be used to categorize documents or label text for further processing. One popular topic modelling
Thijs Veugen, Thijs Veugen, Vincent Dunning, Michiel Marcus, Bart Kamphorst   +4 more
doaj   +1 more source

Italiano

, 2023
openNel seguente elaborato verrano presentate tecniche di NLP su dati relativi a podcast di Spotify. I podcast rappresentano una vasta e crescente raccolta di dialoghi audio.
TORI, GIANLUCA IVO
core  

Supervised Topic Models

, 2010
We introduce supervised latent Dirichlet allocation (sLDA), a statistical model of labelled documents. The model accommodates a variety of response types. We derive an approximate maximum-likelihood procedure for parameter estimation, which relies on variational methods to handle intractable posterior expectations.
David M. Blei, Jon D. McAuliffe
openaire   +3 more sources

Topic Modelling Games [PDF]

, 2020
This paper presents a new topic modelling framework inspired by game theoretic principles. It is formulated as a normal form game in which words are represented as players and topics as strategies that the players select. The strategies of each player are modelled with a probability distribution guided by a utility function that the players try to ...
openaire   +3 more sources

Leveraging Social Media Data to Understand COVID-19 Prevention Measures in Construction: A Machine Learning Approach

Buildings
The COVID-19 pandemic was a particularly challenging time for the construction industry as it experienced significant disruptions to operations, affecting various stakeholders.
Emmanuel B. Boateng, Daniel Oteng, Dan N. O. Bonsu, Vinod Gopaldasani   +3 more
doaj   +1 more source

Dataset Topic modelling De Gids

, 2019
Dataset accompanying 'Van Wissen, L. (2019). Topic Modelling “De Gids”: An Explorative Study into the Use of Topic Modelling on a Cultural Periodical. Research Master Thesis, Vrije Universiteit Amsterdam.' (included as pdf) Usage See the 'experiment_1',
van Wissen, Leon
core   +1 more source

An Iterative Approach to Topic Modelling [PDF]

Topic modelling has become increasingly popular for summarizing text data, such as social media posts and articles. However, topic modelling is usually completed in one shot. Assessing the quality of resulting topics is challenging.
Wong, Albert, Cheng, Florence Wing Yau, Keung, Ashley, Hercules, Yamileth, Lim, Yew-Wei, Pham, Lien, Garcia, Mary Alexandra   +6 more
core   +1 more source

Visualizing Topic Uncertainty in Topic Modelling

, 2023
Word clouds became a standard tool for presenting results of natural language processing methods such as topic modelling. They exhibit most important words, where word size is often chosen proportional to the relevance of words within a topic.
Winker, Peter
core