Exploring supervised and unsupervised methods to detect topics in biomedical text

Background: Topic detection is a task that automatically identifies topics (e.g., "biochemistry" and "protein structure") in scientific articles based on information content. Topic detection will benefit many other natural language processing tasks including information retrieval, text summarization and question answering; and is a necessary step towards the building of an information system that provides an efficient way for biologists to seek information from an ocean of literature. Results: We have explored the methods of Topic Spotting, a task of text categorization that applies the supervised machine-learning technique na

• Type: Journal
• Year: 2006
• Where: BMCBI
• Authors: Minsuk Lee, Weiqing Wang, Hong Yu
• Keywords: BMCBI 2006, Topic Clustering, Topic Detection, Topic Spotting