Results 1 to 10 of about 13,047 (256)
Secure latent Dirichlet allocation [PDF]
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 +4 more
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Latent Dirichlet Allocation modeling of environmental microbiomes. [PDF]
Interactions between stressed organisms and their microbiome environments may provide new routes for understanding and controlling biological systems. However, microbiomes are a form of high-dimensional data, with thousands of taxa present in any given ...
Anastasiia Kim +3 more
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Application of Latent Dirichlet Allocation (LDA) for clustering financial tweets [PDF]
Sentiment classification is one of the hottest research areas among the Natural Language Processing (NLP) topics. While it aims to detect sentiment polarity and classification of the given opinion, requires a large number of aspect extractions.
Fatima-Zahrae Sifi +2 more
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Pengamatan Tren Ulasan Hotel Menggunakan Pemodelan Topik Berbasis Latent Dirichlet Allocation
Ketepatan dalam mengekstrak dan meringkas ribuan ulasan ke dalam beberapa topik menjadi kunci dalam pelaksanaan pengolahan data dan informasi lebih lanjut.
Suparyati Suparyati +2 more
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To investigate the advancements of artificial intelligence techniques in the realm of library and information subject, we have chosen the Latent Dirichlet Allocation method as a case study to explore its current study status and implementations ...
Xinzhou Pan, Yu Xu
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Web content topic modeling using LDA and HTML tags [PDF]
An immense volume of digital documents exists online and offline with content that can offer useful information and insights. Utilizing topic modeling enhances the analysis and understanding of digital documents.
Hamza H.M. Altarturi +2 more
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A Spectral Algorithm for Latent Dirichlet Allocation [PDF]
The problem of topic modeling can be seen as a generalization of the clustering problem, in that it posits that observations are generated due to multiple latent factors (e.g., the words in each document are generated as a mixture of several active topics, as opposed to just one).
Anima Anandkumar +4 more
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This article develops a baseline on how to analyse the statements of monetary policy from Lesotho’s Central Bank using a method of topic classification that utilizes a machine learning algorithm known as Latent Dirichlet Allocation.
Damane Moeti
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Text Categorization Based on Topic Model [PDF]
In the text literature, many topic models were proposed to represent documents and words as topics or latent topics in order to process text effectively and accurately.
Shibin Zhou, Kan Li, Yushu Liu
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Semantic N-Gram Topic Modeling [PDF]
In this paper a novel approach for effective topic modeling is presented. The approach is different fromtraditional vector space model-based topic modeling, where the Bag of Words (BOW) approach is followed.The novelty of our approach is that in phrase ...
Pooja Kherwa, Poonam Bansal
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