The Statistical Evaluation Of Retrieval Efficiency From

随着生物信息的增长，数据库检索的效率已经成为生物企业的核心。特别是，人们可以改变检索方法，并且必须能够评估这种改变是否是一种改进。我们正在开发基于统计引导的方法，以分配数据库检索改进的统计意义。该方法基于描述自举下接收器操作特性曲线[n]的行为的数学中心极限定理。特别是，我们的方法已经被应用于确定PSI-BLAST程序的哪些变化实际上构成了改进。此外，我们正在调查的“等渗性”的相关性检索，假设相关性的秩平均后，记录检索的相关性降序平均。保序假设影响检索效率的评估，初步结果表明，尽管它被广泛采用，假设可能是错误的。我们还在探索将度量标准放在检索方法上的可能性，以确定两种检索方法的密切相关程度。这些指标可以区分，例如，从一个真正新颖的算法（产生一个“遥远的”检索）对一个公认的检索算法（产生“接近”该算法的检索）进行“调整”。

With the growth of biological information, the efficiency of database retrieval has become central to the biological enterprise. In particular, one can change a retrieval method and must be able to evaluate whether the change is an improvement or not. We are developing methods based on the statistical bootstrap to assign statistical significance to improvements in database retrieval. The methods are based on mathematical central limit theorems describing the behavior of the receiver operating characteristic curve [n] under bootstrapping. In particular, our methodology has already been applied to determine which changes to the PSI-BLAST program actually constitute improvements. In addition, we are investigating "isotonicity" of relevance in retrieval, the assumption that after rankwise averaging of relevance, records are retrieved on average in decreasing order of relevance. The isotonic assumption affects the evaluation of retrieval efficiency, and preliminary results indicate that despite its widespread adoption, the assumption can be wrong. We are also exploring the possibility of placing metrics on retrieval methods, to determine how closely related two retrieval methods are. The metrics could distinguish, e.g., a "tweak" on an accepted retrieval algorithm (which produces retrieval "close" to the algorithm's) from a truly novel algorithm (which produces a "distant" retrieval).