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Emerging Research Topic Detection Using Filtered-LDA
2021
AI
Comparing two sets of documents to identify new topics is useful in many applications, like discovering trending topics from sets of scientific papers, emerging topic detection in microblogs, and interpreting sentiment variations in Twitter. In this paper, the main topic-modeling-based approaches to address this task are examined to identify limitations and necessary enhancements. To overcome these limitations, we introduce two separate frameworks to discover emerging topics through a filtered
doi:10.3390/ai2040035
fatcat:o3q4iigsqnab3m7dab7seyzeoa