Exploring supervised and unsupervised methods to detect topics in biomedical text.

ABSTRACT:

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 naïve Bayes to assign automatically a document into one or more predefined topics; and Topic Clustering, which apply unsupervised hierarchical clustering a

SUBMITTER: Lee M 

PROVIDER: S-EPMC1472693 | biostudies-literature | 2006 Mar

REPOSITORIES: biostudies-literature