Results 41 to 50 of about 17,652,183 (292)
Frontiers in Psychology, 2022 PurposeThis study analyzes the topic and distribution features of public information needs for the COVID-19 vaccine from Chinese online Q&A communities and portals.
Lin Wang, Zuquan Xian, Tianyu Du
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A Nested Chinese Restaurant Topic Model for Short Texts with Document Embeddings
Applied Sciences, 2021 In recent years, short texts have become a kind of prevalent text on the internet. Due to the short length of each text, conventional topic models for short texts suffer from the sparsity of word co-occurrence information.
Yue Niu, Hongjie Zhang, Jing Li
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CoRR, 2011 Latent Dirichlet Allocation models discrete data as a mixture of discrete distributions, using Dirichlet beliefs over the mixture weights. We study a variation of this concept, in which the documents' mixture weight beliefs are replaced with squashed Gaussian distributions.
Hennig, P. +3 more
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Study on the Technology Trend Screening Framework Using Unsupervised Learning
Applied Sciences, 2022 Outliers that deviate from a normal distribution are typically removed during the analysis process. However, the patterns of outliers are recognized as important information in the outlier detection method.
Junseok Lee, Sangsung Park, Juhyun Lee
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, 2021 This is a repository for the data generated from the model and the analysis, and the figures, from https://github.com/tuanpham96/topic ...
Tuan Pham (11760959)
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Comparison of Topic Modelling Approaches in the Banking Context
Applied Sciences, 2023 Topic modelling is a prominent task for automatic topic extraction in many applications such as sentiment analysis and recommendation systems. The approach is vital for service industries to monitor their customer discussions.
Bayode Ogunleye +4 more
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CoRR, 2010 The syntactic topic model (STM) is a Bayesian nonparametric model of language that discovers latent distributions of words (topics) that are both semantically and syntactically coherent. The STM models dependency parsed corpora where sentences are grouped into documents.
Jordan L. Boyd-Graber, David M. Blei
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Polylingual topic models [PDF]
Proceedings of the 2009 Conference on Empirical Methods in Natural Language Processing Volume 2 - EMNLP '09, 2009 Topic models are a useful tool for analyzing large text collections, but have previously been applied in only monolingual, or at most bilingual, contexts. Meanwhile, massive collections of interlinked documents in dozens of languages, such as Wikipedia, are now widely available, calling for tools that can characterize content in many languages.
Mimno, David +4 more
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Language Models Explain Word Reading Times Better Than Empirical Predictability
Frontiers in Artificial Intelligence, 2022 Though there is a strong consensus that word length and frequency are the most important single-word features determining visual-orthographic access to the mental lexicon, there is less agreement as how to best capture syntactic and semantic factors. The
Markus J. Hofmann +4 more
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