Results 31 to 40 of about 988,863 (326)
Evaluation of unsupervised static topic models’ emergence detection ability [PDF]
Detecting emerging topics is crucial for understanding research trends, technological advancements, and shifts in public discourse. While unsupervised topic modeling techniques such as Latent Dirichlet allocation (LDA), BERTopic, and CoWords clustering ...
Xue Li +5 more
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The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling
In the era of big data and ubiquitous internet connectivity, user feedback data plays a crucial role in product development and improvement. However, extracting valuable insights from the vast pool of unstructured text data found in user feedback ...
Mohammad Hamid Asnawi +3 more
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Marketing Insights from Reviews Using Topic Modeling with BERTopic and Deep Clustering Network
The feedback shared by consumers on e-commerce platforms holds immense value in marketing, as it offers insights into their opinions and preferences, which are readily accessible.
Yusung An, Hayoung Oh, Joosik Lee
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Modeling Topic and Role Information in Meetings using the Hierarchical Dirichlet Process [PDF]
. In this paper, we address the modeling of topic and role information in multiparty meetings, via a nonparametric Bayesian model called the hierarchical Dirichlet process.
Huang, Songfang, Renals, Steve
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In the history of information and technology the knowledge which was generated is stored in the form of digital technology. In present day the search engines will search based on terms and extract the list of similar documents from many topics. In this paper, the proposed Topic Modelling techniques will search based on the group of words from each ...
Paul Thompson, Susan Hunston
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The Men’s Rights Activism (MRA) movement and its sub-movement The Red Pill (TRP), has flourished online, offering support and advice to men who feel their masculinity is being challenged by societal shifts.
J. B. Mountford
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Topic Modeling: Perspectives From a Literature Review
Topic modeling is a Natural Language Processing technique that has gained popularity over the last ten years, with applications in multiple fields of knowledge.
Andres M. Grisales A. +2 more
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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.
Wang, JianYu, Zhang, Xiao-Lei
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Deutsch-japanische Leitmotivstrukturen in digitalisierten Übersetzungskorpora
Am Beispiel einer Probestudie zum Topic Modeling japanischer Thomas Mann-Übersetzungen reflektiert das Arbeitspapier Möglichkeiten und Herausforderungen einer digitalen Literaturforschung. Eine sich an Ramsays algorithmic criticism orientierende, de- und
Mueller, Nicole M.
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Efficient Correlated Topic Modeling with Topic Embedding
Correlated topic modeling has been limited to small model and problem sizes due to their high computational cost and poor scaling. In this paper, we propose a new model which learns compact topic embeddings and captures topic correlations through the ...
Berg-Kirkpatrick, Taylor +4 more
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