Selection of the Optimal Number of Topics for LDA Topic Model—Taking Patent Policy Analysis as an Example [PDF]
This study constructs a comprehensive index to effectively judge the optimal number of topics in the LDA topic model. Based on the requirements for selecting the number of topics, a comprehensive judgment index of perplexity, isolation, stability, and ...
Jingxian Gan, Yong Qi
doaj +7 more sources
An adaptive method for determining the optimal number of topics in topic modeling [PDF]
Topic models have been successfully applied to information classification and retrieval. The difficulty in successfully applying these technologies is to select the appropriate number of topics for a given corpus.
Yang Xu+3 more
doaj +5 more sources
Topic models with elements of neural networks: investigation of stability, coherence, and determining the optimal number of topics [PDF]
Topic modeling is a widely used instrument for the analysis of large text collections. In the last few years, neural topic models and models with word embeddings have been proposed to increase the quality of topic solutions.
Sergei Koltcov+3 more
doaj +6 more sources
An Adaptive LDA Optimal Topic Number Selection Method in News Topic Identification [PDF]
Nowadays, news text information is exploding, and people need more and more heterogeneous news content. Therefore, news text topic identification is needed to help viewers quickly and accurately screen and filter news related to their interests to save ...
Mingming Zheng+3 more
doaj +3 more sources
Text mining and topic analysis algorithms which group textual contents in the most efficient way, are becoming increasingly useful to summarise the main information contained in large data corpus of complex scientific fields.
Barbara Contiero+2 more
doaj +4 more sources
A fast algorithm with minimax optimal guarantees for topic models with an unknown number of topics [PDF]
We propose a new method of estimation in topic models, that is not a variation on the existing simplex finding algorithms, and that estimates the number of topics K from the observed data. We derive new finite sample minimax lower bounds for the estimation of A, as well as new upper bounds for our proposed estimator. We describe the scenarios where our
Bing, Xin+2 more
+9 more sources
Fractal approach for determining the optimal number of topics in the field of topic modeling.
In this paper we apply multifractal formalism to the analysis of statistical behaviour of topic models under condition of varying number of topics. Our analysis reveals the existence of two self-similar regions and one transition region in the function of density-of-states depending on the number of topics.
Ignatenko, Vera+3 more
openaire +5 more sources
Topic modeling is an unsupervised machine learning technique successfully used to classify and retrieve textual data. However, the performance of topic models is sensitive to selecting optimal hyperparameters, the number of topics 'K' and Dirichlet priors 'α' and 'β.' This data-driven analysis aims to determine the optimum number of topics, 'K,' within
Astha Goyal, Indu Kashyap
openaire +3 more sources
This project explores the application of sophisticated topic models to determine the ideal amount of subjects and evaluate them across several datasets pertaining to trends and current events. We propose a comprehensive approach that leverages the topic models such as Latent Dirichlet Allocation (LDA), Non-negative Matrix Factorization (NMF), Latent ...
G. Manasa
openaire +2 more sources
Topic modeling and content analysis of people’s anxiety-related concerns raised on a computer-mediated health platform [PDF]
Background About one in four Chinese people might suffer or have already suffered from anxiety conditions, with a lifetime prevalence rate of 4.8%. However, many of those who could have benefited from psychological or pharmacological treatments fail to ...
Yi Liu+7 more
doaj +2 more sources