Effective and Efficient Query Processing over Dynamic Social Networks

通过动态社交网络进行有效且高效的查询处理

• 批准号: DP160102114
• 负责人: Dr Timoleon Sellis
• 金额: $ 18.92万
• 依托单位: Swinburne University of Technology
• 依托单位国家: 澳大利亚
• 项目类别: Discovery Projects
• 财政年份: 2016
• 资助国家: 澳大利亚
• 起止时间: 2016-10-05 至 2019-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP160102114
• 关键词: Effective; Efficient; Query; Processing; over

This project aims to invent novel query-based social network data exploration techniques which would help individuals or organisations make smart decisions based on data from increasingly massive, complex and dynamic social networks. Expected project outcomes are formal result semantics, advanced indices, efficient query evaluation algorithms and scalable techniques for three types of commonly used queries. The project plans to develop a system prototype to evaluate the effectiveness and efficiency of the proposed approaches and techniques. Query-based dynamic social network data exploration techniques developed in this project may have practical applications including event and influential topic discovery and tracking, buying trend analysis and political issues analysis.

该项目旨在发明新颖的基于查询的社交网络数据探索技术，帮助个人或组织根据日益庞大，复杂和动态的社交网络数据做出明智的决策。预期的项目成果是正式的结果语义，先进的索引，高效的查询评估算法和可扩展的技术，为三种常用的查询。该项目计划开发一个系统原型，以评估拟议方法和技术的有效性和效率。本研究所开发的基于查询的动态社会网络数据挖掘技术具有实际应用价值，包括事件和有影响力的主题发现和跟踪、购买趋势分析和政治问题分析。