Niche Finding - A New Task of Knowledge Discovery

许多数据驱动的知识发现任务的出发点是一个数据矩阵，它的行是个体，列是数字和/或符号特征，条目是特征值。发现或数据分析的通常目标包括寻找分类器、簇、关联规则和贝叶斯网络。PI在这项工作中提出的关于数据矩阵的新问题是：给定一个特别感兴趣的个人(或行)，该个人的独特之处在哪里？也就是说，在整体环境中简明扼要地阐明个人的利基。PI打算在这里解决的一个挑战是，更好地理解人们倾向于发现哪些关于个人独特性的陈述是可以理解和有趣的。初步结果表明，这两个性质的标准大多是一般性的，只有部分依赖于领域。使用集合覆盖方法的生态位发现的原型实现已经应用于新组装的由123个特征描述的236所美国主要大学的数据集。PI将通过添加新的特征类型、扩大到更大的数据集、比较替代方法和不同的近似算法，以及通过将小生境发现应用于科学和其他专业领域的重大问题来扩展方法。总体目标是像其他人提到的那样，让利基市场像往常一样成为一项发现任务。PI希望表明，对于在科学和其他专业领域具有广泛适用性的数据集，有一个新的、简单和有趣的问题需要提出。他还打算通过开发棒球的特殊版本来提高公众对知识发现和信息处理的鉴赏力，并计划在公共媒体上使用，并作为博物馆展览

The starting point for many tasks of data-driven knowledge discovery is a data matrix whose rows are individuals, columns are numeric and/or symbolic features, and entries are feature values. The usual goals of discovery or data analysis include finding classifiers, clusters, association rules, and Bayesian networks. The new question posed by the PI in this work about a data matrix is: Given one individual (or row) that is of special interest, what is unique about that individual? That is, concisely articulate that individual's niche within the overall context. One challenge the PI intends to address here is to better understand what statements of individual uniqueness people tend to find understandable and interesting. Preliminary results indicate that the criteria for these two properties are mostly general, and only partly domain-dependent. A prototype implementation of niche finding, using a set covering approach, has been applied to a newly assembled dataset on 236 major U.S. universities described by 123 features. The PI will extend the methods by adding new feature types, scaling up to larger datasets, comparing against alternative approaches and different approximation algorithms, and by applying niche finding to significant problems in science and other professional fields. The overall goal is to make niche finding as usual a discovery task as the others cited. The PI expects to show that there is a new, simple, and interesting question to ask about datasets that has broad applicability in science and other professional fields. He also intends to enhance public appreciation for knowledge discovery and information processing by developing special versions for baseball, with plans for use on public media and as a museum exhibit