Results 11 to 20 of about 17,652,183 (292)
A Topic Coverage Approach to Evaluation of Topic Models [PDF]
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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Recurrent Embedded Topic Model
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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Automatic topic detection strategy for information retrieval in spoken document [PDF]
This paper suggests an alternative solution for the task of spoken document retrieval (SDR). The proposed system runs retrieval on multi-level transcriptions (word and phone) produced by word and phone recognizers respectively, and their outputs are ...
Misra, H. +3 more
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topicmodels: An R Package for Fitting Topic Models [PDF]
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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Topic Model Combining Topic Word Embedding and Attention Mechanism [PDF]
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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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
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
doaj +1 more source
Topic Models with Topic Ordering Regularities for Topic Segmentation [PDF]
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
openaire +1 more source
Managing large collections of documents is an important problem for many areas of science, industry, and culture. Probabilistic topic modeling offers a promising solution. Topic modeling is an unsupervised machine learning method that learns the underlying themes in a large collection of otherwise unorganized documents.
Allison June-Barlow Chaney +1 more
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Micro-blog topic detection algorithm based on topic model
Micro-blog data has the characteristic of real-time,volume,short-text,and noise-rich.So it is a challenge for the traditional topic detection technology.A novel micro-blog topic detection algorithm based on topic model was proposed.Firstly,the micro-blog
Hua-jun HUANG +2 more
doaj +3 more sources

