"- the first document belongs to 4th topic. \n", "- the second document belongs to 4th topic. \n", "- the third document belongs to 6th topic. \n", ...

Abstract: Author-topic modeling explores relationships among authors, documents, topics, and words. While traditional Bayesian methods extended Latent Dirichlet Allocation (LDA), recent neural ...

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The Master of Information Management and Systems (MIMS) program educates information professionals to provide leadership for an information-driven world. The Master of Information and Data Science ...

Abstract: Topic modeling is widely used approach for identifying latent topics in large textual dataset. For improved topic extraction and representations, this work introduces an advanced topic ...

Disturbances to the gut microbiome contribute to health conditions like inflammatory bowel disease (IBD). To better understand how those microbes interact with each other and their environment, ...

While many low-income countries (LICs) have built good momentum since 2000, they still face numerous macroeconomic challenges and vulnerabilities. For instance, LICs are currently facing a crisis like ...

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An efficient analysis pipeline, integrating topic modeling with large language model (LLM) summarizing and human verification, was applied to identify the discussion topics. Results: We analyzed 1765 ...

We applied BERTopic with the all-MiniLM-L6 model and k-means clustering to infer thematic structures and used coherence scores to determine the optimal number of topics for each language. Descriptive ...