Automated web data extraction for Canadian fundraising institutions

加拿大筹款机构的自动网络数据提取

• 批准号: 460835-2013
• 负责人: Benlamri, Rachid
• 金额: $ 1.82万
• 依托单位: Lakehead University
• 依托单位国家: 加拿大
• 项目类别: Engage Grants Program
• 财政年份: 2013
• 资助国家: 加拿大
• 起止时间: 2013-01-01 至 2014-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=542321
• 关键词: Automated; web; data; extraction; Canadian

For most business, the volume of useful data available on the Web that can boost their competitive intelligence is an overpowering aspect that needs to be taken into consideration. Unfortunately, search engines, such as Google, can only provide a small fraction of that knowledge. Search engines cannot provide the desired content in a concise and appropriate format. Also, it is not possible to carry out such tedious data extraction task manually by going through every relevant piece of data available on the Web. This is a time consuming and errorprone task that often leads to inaccurate results. So, there is

对于大多数企业来说，网络上提供的大量有用数据可以提高他们的竞争情报，这是一个需要考虑的压倒性因素。不幸的是，搜索引擎，如谷歌，只能提供一小部分的知识。搜索引擎无法以简洁和适当的格式提供所需的内容。此外，不可能通过浏览Web上可用的每一条相关数据来手动执行这种繁琐的数据提取任务。这是一项耗时且容易出错的任务，通常会导致不准确的结果。所以，