Results 11 to 20 of about 3,030,763 (202)
A topic modelling tool was adapted to requirements for a collection of Swedish folk legends. To offer an overview of a list of folk legend texts, which had been automatically extracted by the topic modelling tool, snippet text versions of the folk ...
Maria Skeppstedt +2 more
doaj +1 more source
We propose an Exclusive Topic Modeling (ETM) for unsupervised text classification, which is able to 1) identify the field-specific keywords though less frequently appeared and 2) deliver well-structured topics with exclusive words. In particular, a weighted Lasso penalty is imposed to reduce the dominance of the frequently appearing yet less relevant ...
Hao Lei, Ying Chen
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Enhancing Big Social Media Data Quality for Use in Short-Text Topic Modeling
With the emergence of microblogging platforms and social media applications, large amounts of user-generated data in the form of comments, reviews, and brief text messages are produced every day.
Belal Abdullah Hezam Murshed +5 more
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Topic Models with Topic Ordering Regularities for Topic Segmentation [PDF]
Documents from the same domain usually discuss similar topics in a similar order. In this paper we present new ordering-based topic models that use generalised Mallows models to capture this regularity to constrain topic assignments. Specifically, these new models assume that there is a canonical topic ordering shared amongst documents from the same ...
Lan Du 0002 +2 more
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Conceptualization Topic Modeling [PDF]
Recently, topic modeling has been widely used to discover the abstract topics in text corpora. Most of the existing topic models are based on the assumption of three-layer hierarchical Bayesian structure, i.e. each document is modeled as a probability distribution over topics, and each topic is a probability distribution over words.
Yi-Kun Tang +3 more
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Topic Modelling in Spontaneous Speech Data [PDF]
The development of large-scale, language corpora has highlighted the increasing need for automated methods, to assist humans in the inefficient task of sorting and labelling language-transcripts by semantic contents (i.e. topics). One
Reverter-Rambaldi, Marcel
core +1 more source
Unsupervised learning of generative topic saliency for person re-identification [PDF]
(c) 2014. The copyright of this document resides with its authors. It may be distributed unchanged freely in print or electronic forms.© 2014. The copyright of this document resides with its authors.
Wang, H +5 more
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Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method that learns the underlying themes in a large collection of otherwise unorganized documents.
Allison June-Barlow Chaney +1 more
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Use of topic modelling to analyze the Euronews Corpus
How can we use topic modelling to study early modern handwritten news sheets?
Toth Gabor Mihaly
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Enhancing topic clustering for Arabic security news based on k‐means and topic modelling
The internet has become one of the main sources of news spread as it unleashed the information dissemination space, where the news websites express opinions on entities while also reporting on recent or unusual security risks.
Adel R. Alharbi +2 more
doaj +1 more source

