Results 31 to 40 of about 3,030,763 (202)
IEEE Access, 2023 The research interest of knowledge in human resource management (HRM) is significant. Bibliometric or systematic literature review studies capture the main areas and trends in the field of HRM. However, many HRM studies work only with a limited number of
Lukas Falat +3 more
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On a Topic Model for Sentences
Proceedings of the 39th International ACM SIGIR conference on Research and Development in Information Retrieval, 2016 Probabilistic topic models are generative models that describe the content of documents by discovering the latent topics underlying them. However, the structure of the textual input, and for instance the grouping of words in coherent text spans such as sentences, contains much information which is generally lost with these models.
Georgios Balikas +2 more
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Probabilistic Topic Models [PDF]
IEEE Signal Processing Magazine, 2010 In this article, we review probabilistic topic models: graphical models that can be used to summarize a large collection of documents with a smaller number of distributions over words. Those distributions are called "topics" because, when fit to data, they capture the salient themes that run through the collection.
David M. Blei +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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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. When topic models are used for discovery of topics in text collections, a question that arises naturally is how well the model-induced topics correspond to topics of interest to the analyst.
Damir Korencic +3 more
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Details of the texts used for topic modelling.
, 2022 Details of the texts used for topic modelling.
Mukul Ranjan (13570238) +1 more
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MITAO: A User Friendly and Modular Software for Topic Modelling [PDF]
, 2020 Texts are among the most relevant data sources for social scientists, and traditionally researchers adopt qualitative methods for dealing with them. Yet, new computer aided techniques offer promising methodological avenues for scholars, which can now ...
Pareschi, Luca +7 more
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Proceedings of the 2022 Conference on Empirical Methods in Natural Language Processing, 2022 We propose a new problem called coordinated topic modeling that imitates human behavior while describing a text corpus. It considers a set of well-defined topics like the axes of a semantic space with a reference representation. It then uses the axes to model a corpus for easily understandable representation. This new task helps represent a corpus more
Pritom Saha Akash +2 more
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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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Exploring the space of topic modelling and topic coherence on short and long text corpora
, 2020 Topic Modelling, a discipline of Natural Language Processing, is widely prevalent and its application on social network communications has become essential in identifying key themes impacting society.
Pathela, Chirag Kumar
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