To supplement k-means and improve topic coherence, we used LDA, a probabilistic topic modelling method that assigns topic distributions to documents and identifies representative keywords for each ...

Changing the prescribing protocol for low-dose aspirin (LDA) for preeclampsia prevention from risk-based to universal significantly increased aspirin use in pregnant patients, based on new data ...

The main objective of this article is to compare user comments from 4 Fintech applications in Indonesia using the Latent Dirichlet Allocation (LDA) algorithm. This research is word processing research ...

The main purpose of this article is to model the topic of OVO Fintech user comments using LDA. This research is a word processing research conducted using text mining. The statistical population is ...

Using the RACE dataset to extract a dominant topic from each document and perform LDA topic modeling in python. With the advent of big data and Machine Learning along with Natural Language Processing, ...

This is a python implementation of LDA using gibbs sampling algorithm. The following picture shows the top 10 words in the 10 topics (set K = 10) generated by this algorithm over 16 sentences about ...

We developed a comprehensive Latent Dirichlet Allocation (LDA) model with 25 topics using natural language processing (NLP) techniques on PubMed ® research articles about “COVID.” We propose a novel ...