Optimal Data Quality
研究了决定所需数据质量的常见假设，在决策理论模型中分析其成立与失败的条件，特别关注用户行为非最优时如何确定所需数据质量。
Abstract Commonly accepted hypotheses guide practical determination of needed data quality; for example, as the probability that a decision uses data increases, the needed data quality increases, and the more rudimentary the uses of the data, the less data quality is needed. These hypotheses are formally defined and analyzed in some decision-theoretic models. Conditions under which the hypotheses hold and fail are examined. Particular attention is given to determining needed data quality when the users of the data behave nonoptimally.