In the pursuit of accurate and scalable quantitative methods for financial market analysis, focus has shifted from individual stock models to those capturing interrelations between companies their stocks. However, current relational are limited by reliance on predefined relationships exclusive consideration immediate effects. To address these limitations, we present a groundbreaking framework a...

Analyzing short texts infers discriminative and coherent latent topics that is a critical fundamental task since many real-world applications require semantic understanding of texts. Traditional long text topic modeling algorithms (e.g., PLSA LDA) based on word co-occurrences cannot solve this problem very well only limited co-occurrence information available in Therefore, has already attracted...

Purpose: This study aimed to understand the keywords and major topics of educational goals objectives nursing institutions in South Korea.Methods: From May 10 20, 2022, all 201 Korea were collected. Using NetMiner program, degree centrality, semantic structure, topic modeling analyzed.Results: The top structures included ‘respect for human (life)-spirit-science-based on, global-competency-profe...