Results 31 to 40 of about 23,589,100 (342)
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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Labeled LDA: A supervised topic model for credit attribution in multi-labeled corpora
Conference on Empirical Methods in Natural Language Processing, 2009 A significant portion of the world's text is tagged by readers on social bookmarking websites. Credit attribution is an inherent problem in these corpora because most pages have multiple tags, but the tags do not always apply with equal specificity ...
Daniel Ramage +3 more
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MetaLDA: A Topic Model that Efficiently Incorporates Meta Information [PDF]
Industrial Conference on Data Mining, 2017 Besides the text content, documents and their associated words usually come with rich sets of meta information, such as categories of documents and semantic/syntactic features of words, like those encoded in word embeddings.
He Zhao +3 more
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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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An Automatic Approach for Document-level Topic Model Evaluation [PDF]
Conference on Computational Natural Language Learning, 2017 Topic models jointly learn topics and document-level topic distribution. Extrinsic evaluation of topic models tends to focus exclusively on topic-level evaluation, e.g. by assessing the coherence of topics.
Shraey Bhatia +2 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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International Journal of Innovative Technology and Exploring Engineering, 2019 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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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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Neural Topic Model with Reinforcement Learning
Conference on Empirical Methods in Natural Language Processing, 2019 In recent years, advances in neural variational inference have achieved many successes in text processing. Examples include neural topic models which are typically built upon variational autoencoder (VAE) with an objective of minimising the error of ...
Lin Gui +5 more
semanticscholar +1 more source
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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