A knowledge-based framework for the management of imprecision in data

用于管理数据不精确性的基于知识的框架

• 批准号: 327545-2011
• 负责人: Kwiatkowska, Bogumila
• 金额: $ 1.02万
• 依托单位: Thompson Rivers University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2011
• 资助国家: 加拿大
• 起止时间: 2011-01-01 至 2012-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=481771
• 关键词: knowledge; based; framework; management; imprecision

Imprecision is intrinsic to many data, especially in complex biological, ecological, and medical systems. Often, real-life decisions are made based on subjective, uncertain, and imprecise data. Thus, the management of imprecision is one of the most critical issues in data sharing, decision making, information disclosure, and data mining. Imprecision has been studied in the context of several disciplines and various methods have been developed to represent imprecise data in databases, and, recently, in the Web repositories. However, the current approaches do not address sufficiently the interpretation of imprecision in the context of domain knowledge. Yet, the interpretation of imprecision is highly contextual. For example, a statement "blood pressure above normal" may be sufficiently precise in one context or it could be insufficient in another context and a measurement such as "160/90" and additional information "no antihypertensive medication" may be needed.

不精确性是许多数据固有的，特别是在复杂的生物、生态和医学系统中。通常，现实生活中的决策是基于主观的，不确定的和不精确的数据。因此，不精确性的管理是数据共享、决策制定、信息披露和数据挖掘中最关键的问题之一。不精确性已经在几个学科的背景下进行了研究，并且已经开发了各种方法来表示数据库中的不精确数据，最近，在Web存储库中。然而，目前的方法并没有充分解决领域知识的背景下的不精确性的解释。然而，对不精确的解释是高度语境化的。例如，“血压高于正常”的陈述在一种情况下可能足够精确，或者在另一种情况下可能不够精确，并且可能需要诸如“160/90”的测量和“没有抗高血压药物”的附加信息。