Application of Latent Dirichlet Allocation (LDA) for clustering financial tweets [PDF]
E3S Web of Conferences, 2021 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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Topic Modeling on Online News.Portal Using Latent Dirichlet Allocation (LDA)
IJCCS (Indonesian Journal of Computing and Cybernetics Systems), 2022 The amount of News displayed on online news portals. Often does not indicate the topic being discussed, but the News can be read and analyzed. You can find the main issues and trends in the News being discussed.
Mohammad Rezza Fahlevvi, Azhari SN
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Implementasi Latent Dirichlet Allocation (LDA) untuk Klasterisasi Cerita Berbahasa Bali [PDF]
Jurnal Teknologi Informasi dan Ilmu Komputer, 2021 Cerita-cerita berbahasa Bali memiliki topik yang beragam namun memuat nilai kearifan lokal yang perlu untuk dilestarikan. Jika cerita-cerita tersebut dapat dikelompokkan berdasarkan topik, tentu akan sangat memudahkan bagi para pembacanya dalam memilih ...
Ngurah Agus Sanjaya ER
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Improving optimal prompt learning through multilayer fusion and latent dirichlet allocation [PDF]
Frontiers in Robotics and AIRecent advances in few-shot learning have demonstrated the potential of prompt-based techniques with pre-trained models, eliminating the need for extensive fine-tuning. However, challenges such as obtaining optimal prompts and addressing data scarcity in
Qinghua Chen +6 more
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The Latent Dirichlet Allocation (LDA) generative model for automating process of rendering judicial decisions [PDF]
E3S Web of Conferences, 2023 The Latent Dirichlet Allocation (LDA) generative model is widely used in statistical analysis and machine learning due to its ability to model the probabilities of multidimensional categorical data, such as the frequencies of different categories or the ...
Pylov Petr +2 more
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Semantic N-Gram Topic Modeling [PDF]
EAI Endorsed Transactions on Scalable Information Systems, 2020 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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Web content topic modeling using LDA and HTML tags [PDF]
PeerJ Computer Science, 2023 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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Enhancing Indonesian customer complaint analysis: LDA topic modelling with BERT embeddings
Jurnal Ilmiah SINERGI, 2023 Social media data can be mining for recommended systems to know the best trends or patterns. The customers have the freedom to ask questions about the product, tell their demands, and convey their complaints through social media.
Mutiara Auliya Khadija +1 more
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TOPIC MODELING AND ASSOCIATION RULE MINING TO DISCOVER GEOSPATIAL SEMANTIC INFORMATION FROM UNSTRUCTURED DATA SOURCES [PDF]
The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, 2022 As the amount of semi-structured and unstructured information sources expands at an exponential rate, there is a growing demand for semantic information elicitation of the immanent knowledge included in these sources.
Ε. Katsadaki, M. Kokla
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Unsupervised segmentation of greenhouse plant images based on modified Latent Dirichlet Allocation [PDF]
PeerJ, 2018 Agricultural greenhouse plant images with complicated scenes are difficult to precisely manually label. The appearance of leaf disease spots and mosses increases the difficulty in plant segmentation.
Yi Wang, Lihong Xu
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