Automatic Text Categorization and Its Applicationto Text

We develop an automatic text categorization approach and investigate its application to text retrieval. The categorization approach is derived from a combination of a learning paradigm known as instancebased learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the e ectiveness of our categorization approach using two real-world document collections from the MEDLINE database. Next we investigate the application of automatic categorization to text retrieval. Our experiments clearly indicate that automatic categorization improves the retrieval performance compared with no categorization. We also demonstrate that the retrieval performance using automatic categorization achieves the same retrieval quality as the performance using manual categorization. Furthermore, detailed analysis of the retrieval performance on each individual test query is provided.