Patent ID: 8650138

Claim:
An active metric learning device for clustering analysis target data having a plurality of attributes, comprising: a metric application data analysis unit which performs calculations and analyses regarding distances between the analysis target data; a metric optimization unit which optimizes correlations and attributes between the analysis target data and outputs the optimized metric matrix; and an attribute clustering unit which performs clustering of the optimized metric matrix according to the attributes, wherein the metric application data analysis unit is formed with: a metric applying module which calculates the distance between the analysis target data by having the analysis target data and a Mahalanobis metric matrix showing the distance between the data as inputs; a data analyzing module which analyzes the data according to a prescribed function by using the distance between the analysis target data and outputs a data analysis result; an analysis result storage module which saves the data analysis result; and a metric matrix structuralizing unit which inputs a metric matrix that is structuralized by approximating the original metric matrix to the metric applying module and the data analyzing module; the metric optimization unit is formed with: a feedback converting module which creates side information according to a feedback command from a user constituted with either the correlations or the attributes between the analysis target data or with a combination thereof; and a metric learning module which creates a metric matrix that is optimized under a prescribed condition based on the created side information; a feedback command from a user regarding the attributes contains information about those that are supposed to belong to a same cluster between the analysis target data and information about a combination of a higher-order concept and a lower-order concept of the analysis target data; the side information contains pair information that is information about data of two points to be in a same pair among the analysis target data, and group information that is information about data of two points or more to be in a same group among the analysis target data; and the attribute clustering unit performs clustering on the metric matrix that is optimized by the metric optimization unit according to the attributes.