1. An information processing apparatus, comprising: a memory that stores a plurality of previously stored images in groups corresponding to a plurality of predetermined event categories, and that stores metadata corresponding to at least one of the plurality of predetermined event categories; extraction means for extracting metadata from a captured image that is not among the plurality of previously stored images; and recognition means for generating a classifier by executing a training algorithm on metadata from a plurality of learning images different from the captured image and for determining an event category corresponding to the captured image from among the plurality of predetermined event categories based on the metadata extracted from the captured image and the classifier generated by the recognition means, wherein the memory stores the captured image in one of the groups of previously stored images corresponding to the event category determined by the recognition means, wherein the classifier and the event category determined by the recognition means are updated based on displaying, with the captured image, typical images selected from the previously stored images, each of the typical images being representative of a distinct event category of the plurality of predetermined event categories, and wherein the groups corresponding to the plurality of predetermined event categories are generated by comparing standard deviations of time information for nodes representing a plurality of images, in accordance with an order specified by a data structure used to store the nodes, and classifying a subset of the nodes in at least one different group, based on comparisons with a predetermined threshold.