Efficient data manipulation in document classification

文档分类中的高效数据操作

• 批准号: LX0346612
• 负责人: Prof Rafael Calvo
• 金额: $ 3.99万
• 依托单位: The University of Sydney
• 依托单位国家: 澳大利亚
• 项目类别: Linkage - International
• 财政年份: 2003
• 资助国家: 澳大利亚
• 起止时间: 2003-01-06 至 2005-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/LX0346612
• 关键词: Efficient; data; manipulation; document; classification

Document Classification has an enormous relevance in an era where large amounts of textual information is available. Document Classification is based on statistical and machine learning techniques that model documents represented as points in a multidimensional space. The Computer Engineering Laboratory (CEL) has ongoing projects using neural networks and other techniques for document classification. We are developing a development environment for large classification tasks, and Prof. Lee¡¯s work will focus in managing large amounts of data for them. Using his experience in data compression, databases and web applications, he will produce a set of tools for handling Gigabytes of textual data in our classification environment.

文档分类在一个大量文本信息可用的时代具有巨大的相关性。文档分类基于统计和机器学习技术，将文档建模为多维空间中的点。计算机工程实验室（CEL）正在进行使用神经网络和其他技术进行文档分类的项目。我们正在开发用于大型分类任务的开发环境，李教授的工作将集中在管理这些任务的大量数据上。”利用他在数据压缩、数据库和web应用程序方面的经验，他将开发一套工具，用于在我们的分类环境中处理千兆字节的文本数据。