Biclique discovery in Big Data

大数据中的 Biclique 发现

• 批准号: DP170104747
• 负责人: Prof Chengfei Liu
• 金额: $ 23.88万
• 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: 2017
• 资助国家: 澳大利亚
• 起止时间: 2017-01-01 至 2021-12-31
• 项目状态: 已结题
• 来源: https://dataportal.arc.gov.au/RGS/Web/Grants/DP170104747
• 关键词: Biclique; discovery; Big; Data

This project aims to design algorithms to capture Big Data. Biclique is a popular graph model that can capture important cohesive structures in many applications. However, traditional biclique discovery algorithms which only focus on simple, small-scale, static and deterministic data are inadequate in the era of Big Data where data has Variety (various formats), Volume (large quantity), Velocity (dynamic update) and Veracity (uncertainty). This project expects to benefit real applications in both public and private sectors and add value to Australian manufactured products.

该项目旨在设计捕获大数据的算法。Biclique是一种流行的图模型，可以在许多应用中捕获重要的内聚结构。然而，传统的biclique发现算法只关注简单、小规模、静态和确定性的数据，在数据具有多样性（各种格式）、容量（大量）、速度（动态更新）和准确性（不确定性）的大数据时代显得力不从心。该项目预计将有利于公共和私营部门的真实的应用，并为澳大利亚制造产品增值。