Data retrieval from massive information structures

海量信息结构中的数据检索

• 批准号: DP140103256
• 负责人: Prof Alistair Moffat
• 金额: $ 21.64万
• 依托单位: The University of Melbourne
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2014
• 资助国家: 澳大利亚
• 起止时间: 2014-01-01 至 2017-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP140103256
• 关键词: Data; retrieval; massive; information; structures

Information search is an essential tool. But most current services regard the data as unstructured collections of independent documents, free of context. Next-generation search applications, such as over social networks, or corporate websites, or XML data sets, must account for the inherent relationships between data items, and must allow the efficient inclusion of search context. Queries should favour semantically local data, giving results that depend on the perceived state of the querier. This project will develop indexing and search techniques for massive structured data sets. The new search methods will incorporate theoretical advances and will be experimentally validated using industry-standard open-source distributed systems.

信息搜索是必不可少的工具。但是，大多数当前的服务将数据视为独立文档的非结构化集合，没有上下文。下一代搜索应用程序（如社交网络、公司网站或XML数据集）必须考虑到数据项之间的内在关系，并且必须允许有效地包含搜索上下文。查询应该倾向于语义上的本地数据，给出的结果取决于查询器的感知状态。该项目将为大规模结构化数据集开发索引和搜索技术。新的搜索方法将结合理论进步，并将使用行业标准的开源分布式系统进行实验验证。