1. A method comprising: analyzing each digital image in a digital image collection to generate associated feature descriptors related to image content or image capture conditions; storing the feature descriptors associated with the digital images in a metadata database; using a data processor to automatically analyze the metadata database to identify a plurality of frequent itemsets, wherein each of the frequent itemsets is a set of co-occurring feature descriptors that occurs in at least a predefined fraction of the digital images, each frequent itemset being associated with a subset of the digital images; determining, for each of the identified frequent itemsets, a probability of occurrence representing a probability that a respective frequent itemset occurs in a general population of images based on one or more probability distributions determined from an analysis of a large number of image collections; determining a quality score for each of the identified frequent itemsets responsive to the determined probability of occurrence; ranking the frequent itemsets based at least on the determined quality scores; identifying one or more groups of related digital images corresponding to one or more of the top ranked frequent itemsets; and storing an indication of the identified groups of related digital images in a processor-accessible memory.