Results 61 to 70 of about 1,143,739 (216)
User–Topic Modeling for Online Community Analysis
Applied Sciences, 2020 Analyzing user behavior in online spaces is an important task. This paper is dedicated to analyzing the online community in terms of topics. We present a user–topic model based on the latent Dirichlet allocation (LDA), as an application of topic modeling
Sung-Hwan Kim, Hwan-Gue Cho
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Knowledge Source Rankings for Semi-Supervised Topic Modeling
Information, 2022 Recent work suggests knowledge sources can be added into the topic modeling process to label topics and improve topic discovery. The knowledge sources typically consist of a collection of human-constructed articles, each describing a topic (article-topic)
Justin Wood, Corey Arnold, Wei Wang
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The Polylingual Labeled Topic Model [PDF]
, 2015 Accepted for publication at KI 2015 (38th edition of the German Conference on Artificial Intelligence)
Arnim Bleier +5 more
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When Topic Models Disagree [PDF]
Proceedings of the 24th International Conference on World Wide Web, 2015 We explore how the unsupervised extraction of topic-related keywords benefits from combining multiple topic models. We show that averaging multiple topic models, inferred from different corpora, leads to more accurate keyphrases than when using a single topic model and other state-of-the-art techniques. The experiments confirm the intuitive idea that a
Sterckx, Lucas +3 more
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Getting Started with Topic Modeling and MALLET
The Programming Historian, 2012 In this lesson you will first learn what topic modeling is and why you might want to employ it in your research. You will then learn how to install and work with the MALLET natural language processing toolkit to do so.
Shawn Graham +2 more
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Comparison of learning analytics and educational data mining: A topic modeling approach
Computers and Education: Artificial Intelligence, 2021 Educational data mining and learning analytics, although experiencing an upsurge in exploration and use, continue to elude precise definition; the two terms are often interchangeably used.
David J. Lemay +2 more
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Analyzing Geographic Questions Using Embedding-based Topic Modeling
ISPRS International Journal of Geo-Information, 2023 Recently, open-domain question-answering systems have achieved tremendous progress because of developments in large language models (LLMs), and have successfully been applied to question-answering (QA) systems, or Chatbots. However, there has been little
Jonghyeon Yang, Hanme Jang, Kiyun Yu
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Neural Topic Modeling with Deep Mutual Information Estimation [PDF]
arXiv, 2022 The emerging neural topic models make topic modeling more easily adaptable and extendable in unsupervised text mining. However, the existing neural topic models is difficult to retain representative information of the documents within the learnt topic representation.
arxiv
, 2016 We develop a privatised stochastic variational inference method for Latent Dirichlet Allocation (LDA). The iterative nature of stochastic variational inference presents challenges: multiple iterations are required to obtain accurate posterior distributions, yet each iteration increases the amount of noise that must be added to achieve a reasonable ...
Park, M. +3 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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