Finding Groups in Big Data

在大数据中寻找群体

• 批准号: RGPIN-2016-04850
• 负责人: Sander, Jörg
• 金额: $ 3.35万
• 依托单位: University of Alberta
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2017
• 资助国家: 加拿大
• 起止时间: 2017-01-01 至 2018-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=634693
• 关键词: Finding; Groups; Big; Data

The main objective of the proposed research program is to advance theory and practice of “Big Data” cluster analysis. “Big Data” refers to today’s ever larger and more complex data sets, which are typically collected on a large scale by automatic equipment (e.g. microarray chips, sensors, logging devices). These data sets have become abundant, and they hold the potential for the discovery of new insights, which can lead to new opportunities for improved, data-driven decision making. Unsupervised, exploratory methods for knowledge discovery play an important role in realizing this potential.

该研究计划的主要目标是推进“大数据”聚类分析的理论和实践。“大数据”指的是当今越来越大、越来越复杂的数据集，通常由自动设备(如微阵列芯片、传感器、记录设备)大规模收集。这些数据集已经变得丰富，它们具有发现新见解的潜力，这可能会带来改进的、数据驱动的决策制定的新机会。无监督的、探索性的知识发现方法在实现这一潜力方面发挥着重要作用。