Results 61 to 70 of about 4,032,512 (303)
senderle/topic-modeling-tool: First stable release
, 2017 <p>This marks the first stable release of the new version of the Topic Modeling Tool. It incorporates all of the features required for general-audience use, and we haven't received any bug reports recently, which constitutes iron-clad scientific ...
David Newman +3 more
core +1 more source
Topic Modeling for Amharic User Generated Texts
Information, 2021 Topic Modeling is a statistical process, which derives the latent themes from extensive collections of text. Three approaches to topic modeling exist, namely, unsupervised, semi-supervised and supervised. In this work, we develop a supervised topic model
Girma Neshir +2 more
doaj +1 more source
Towards Topic Modeling Swedish Housing Policies
Digital Humanities in the Nordic and Baltic Countries Publications, 2018 Topic modeling is an unsupervised method for finding topics in large collections of data. However, in most studies which employ topic modeling there is a lack of using linguistic information when preprocessing the data.
Anna Lindahl, Love Börjeson
doaj +1 more source
The World of Topic Modeling in R
Medien & Kommunikationswissenschaft, 2022 This software review provides a systematic overview of R packages for topic modeling. These packages facilitate the application of computational text analysis to conduct research compatible with a wide variety of methodological frameworks employed in the
Gregor Wiedemann
doaj +1 more source
CoRR, 2016 Recently there has been significant activity in developing algorithms with provable guarantees for topic modeling. In standard topic models, a topic (such as sports, business, or politics) is viewed as a probability distribution $\vec a_i$ over words, and a document is generated by first selecting a mixture $\vec w$ over topics, and then generating ...
Avrim Blum, Nika Haghtalab
openaire +2 more sources
Multi-Machine Gaussian Topic Modeling for Predictive Maintenance
IEEE Access, 2021 In this paper, we propose a coherent framework for multi-machine analysis, using a group clustering model, which can be utilized for predictive maintenance (PdM). The framework benefits from the repetitive structure posed by multiple machines and enables
Alexander Karlsson +2 more
doaj +1 more source
Neurocomputing, 2023 Nonnegative matrix factorization (NMF) based topic modeling methods do not rely on model- or data-assumptions much. However, they are usually formulated as difficult optimization problems, which may suffer from bad local minima and high computational complexity.
Jianyu Wang, Xiao-Lei Zhang 0001
openaire +2 more sources
Pediatric Blood &Cancer, EarlyView.ABSTRACT Background Loneliness is associated with adverse physical and mental health outcomes and remains understudied in children and adolescents undergoing cancer therapy. Pediatric oncology patients may be at increased risk due to medical isolation and disruption of social networks.
Charlotte N. Stahlfeld +5 more
wiley +1 more source
Systematic Literature Review of Topic Labeling
IEEE AccessThe rapid growth of textual data on the web has led researchers to develop methods in Natural Language Processing (NLP) to process, understand, and identify topics.
Salma Mekaoui +3 more
doaj +1 more source
On-line Evolutionary Sentiment Topic Analysis Modeling
International Journal of Computational Intelligence Systems, 2018 As the rapid booming of reviews, a valid sentiment analysis model will significantly boost the review recommendation system’s capability, and present more constructive information for consumers.
YongHeng Chen +3 more
doaj +1 more source