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Recurrent Embedded Topic Model
Applied Sciences, 2023 In this paper we propose the Recurrent Embedded Topic Model (RETM) which is a modification of the Embedded Topic Modelling (ETM) by reusing the Continuous Bag of Words (CBOW) that the model had implemented and applying it to a recurrent neural network ...
Carlos Vargas, Hiram Ponce
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A Topic Coverage Approach to Evaluation of Topic Models [PDF]
IEEE Access, 2021 Topic models are widely used unsupervised models capable of learning topics – weighted lists of words and documents – from large collections of text documents.
Damir Korencic +3 more
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Language Model-Driven Topic Clustering and Summarization for News Articles
IEEE Access, 2019 Topic models have been widely utilized in Topic Detection and Tracking tasks, which aim to detect, track, and describe topics from a stream of broadcast news reports.
Peng Yang, Wenhan Li, Guangzhen Zhao
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topicmodels: An R Package for Fitting Topic Models
Journal of Statistical Software, 2011 Topic models allow the probabilistic modeling of term frequency occurrences in documents. The fitted model can be used to estimate the similarity between documents as well as between a set of specified keywords using an additional layer of latent ...
Bettina Grun, Kurt Hornik
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Dynamic joint sentiment-topic model [PDF]
ACM Transactions on Intelligent Systems and Technology, 2013 Social media data are produced continuously by a large and uncontrolled number of users. The dynamic nature of such data requires the sentiment and topic analysis model to be also dynamically updated, capturing the most recent language use of sentiments ...
Yulan He, Chenghua Lin, Kam-Fai Wong
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Selection of the Optimal Number of Topics for LDA Topic Model-Taking Patent Policy Analysis as an Example. [PDF]
Entropy (Basel), 2021 Gan J, Qi Y.
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Topic Model Combining Topic Word Embedding and Attention Mechanism [PDF]
Jisuanji gongcheng, 2020 With the popularity of social software,mining effective information from massive digital documents has been a hotspot.The classic topic models including LDA and LSA capture topic information based on word co-occurrence and ignore the context information ...
QIN Tingting, LIU Zheng, CHEN Kejia
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Applied Sciences, 2023 As the main driving force for the digital transformation of the construction industry, the uncertainty of digital technology in the application process has seriously hindered the high-quality development of the construction industry.
Hui Li +5 more
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The Combination of Contextualized Topic Model and MPNet for User Feedback Topic Modeling
IEEE Access, 2023 In the era of big data and ubiquitous internet connectivity, user feedback data plays a crucial role in product development and improvement. However, extracting valuable insights from the vast pool of unstructured text data found in user feedback ...
Mohammad Hamid Asnawi +3 more
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Topic Models with Topic Ordering Regularities for Topic Segmentation [PDF]
2014 IEEE International Conference on Data Mining, 2014 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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