Web content topic modeling using LDA and HTML tags.

ABSTRACT: An immense volume of digital documents exists online and offline with content that can offer useful information and insights. Utilizing topic modeling enhances the analysis and understanding of digital documents. Topic modeling discovers latent semantic structures or topics within a set of digital textual documents. The Internet of Things, Blockchain, recommender system, and search engine optimization applications use topic modeling to handle data mining tasks, such as classification and clustering. The usefulness of topic models depends on the quality of resulting term patterns and topics with high quality. Topic coherence is the standard metric to measure the quality of topic models. Previous studies build topic models to generally work on conventional documents, and they are insufficien

SUBMITTER: Altarturi HHM 

PROVIDER: S-EPMC10403181 | biostudies-literature | 2023

REPOSITORIES: biostudies-literature