CIF:EAGER:Information Theory Approaches for finding Atypical Sequences

信息时代的一个特征是信息呈指数级增长，这些信息可以通过网络随时获得，从而产生了“大数据”时代。虽然处理如此大量的数据的传统方法是通过统计，如平均值，但这个项目的观点是相反的，即信息中的大多数价值都在偏离平均值的部分，这些部分是不寻常的、非典型的。常见的例子包括偏离规范的有价值的绘画或作品，这些都是非典型的。风险开发和科学研究可能也是如此。这个项目的目标是从理论和实践两个角度来研究非典型性。该工作使用一般意义上的描述长度的信息论概念来刻画非典型性。该项目围绕两个方面展开。首先是一种理论发展，从信息论的角度准确地确定了应该被视为非典型的东西。第二是实现这一理论的算法开发，特别是寻找快速算法来实现，以便处理大数据集。对大数据集的分析将用于模拟，因为它们可以带来人类心脏病的新诊断方法。大数据集主要用于生物学和医学，包括心电图和基因组学。

One characteristic of the information age is the exponential growth of information, and the ready availability of this information through networks, giving the "Big Data" era. Whereas the conventional approach to treating such large volumes of data is through statistics, such as averages, the perspective in this project is the opposite, namely that most of the value in the information is in the parts that deviate from the average, that are unusual, atypical. Familiar examples include valuable paintings or writings that deviate from the norms, that are atypical. The same could be true for venture development and scientific research. The goal of this project is to investigate atypicality both from a theoretical and a practical point of view. The proposed work uses the information theory concept of descriptive length, in a general sense, to characterize atypicality. The project is oriented around two thrusts. The first is a theoretical development to make precise exactly what should be considered atypical from an information theory point of view. The second is algorithm development to implement this theory, and in particular to find fast algorithms for implementation so that big data sets can be processed.Analysis of large data sets, mainly in biology and medicine, including ECG (electro cardiogram) and genomics, will be used in simulations, as they can lead to new diagnostic methods for human cardiac disease.