.png){kind=icon}
返回
Automatic text categorization and its application to text retrieval
.png){kind=icon}
PRE
AI
DOI：10.1109/69.824599.png)
.png){kind=icon}
原文求助.png){kind=icon}
分享.png){kind=icon}
收藏
摘要
En 中文
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 instance-based learning and an advanced document retrieval technique known as retrieval feedback. We demonstrate the effectiveness 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.
Keyword:
text categorization
automatic classification
text retrieval
instance-based learning
query processing
AI总结
对已上传原文的论文进行重点信息的提取，主要内容包括：简要概述、研究摘要、背景介绍、关键亮点、图文解析、展望与总结。
期刊
IF:
10.4
论文数:
6.8K
被引数:
3.2W
机构
暂无机构信息
引用论文
.png){kind=icon}
分享收藏
分享收藏分享收藏
分享收藏
查看更多内容