Patent attributes
An approach is provided for fully-automated learning to match heterogeneous feature spaces for mapping. The approach involves determining a first feature space comprising first features and a second feature space comprising second features, and classified by a feature detector into a first attribution category and a second attribution category, respectively. The approach further involves calculating a first similarity score for the first feature space based on a first distance metric applied to the first features, and a second similarity score for the second feature space based on a second distance metric applied to the second features. The approach also involves determining a transformation space comprising a first weight to be applied to the first similarity score and a second weight to be applied to the second similarity score based on matching the first attribution category and the second attribution category.
