17. A computer-implemented process for comparing the annotation precision of two different automatic image annotation (AIA) algorithms, comprising using a computing device to perform the following process actions: inputting a set T of images; manually applying ground-truth keyword annotations to each image in T, wherein T comprises a total number of images given by n; utilizing a first AIA algorithm to automatically generate first keyword annotations for each image in T; utilizing a second AIA algorithm to automatically generate second keyword annotations for each image in T; computing a first pair-wise semantic distance score SD( ) for each image in T, wherein said first score SD( ) specifies a metric for a semantic distance between the first keyword annotations and the ground-truth keyword annotations; computing a second pair-wise semantic distance score SD( ) for each image in T, wherein said second score SD( ) specifies a metric for the semantic distance between the second keyword annotations and the ground-truth keyword annotations; and generating a semantic relative comparative score (RCS) which compares the annotation precision of the first and second AIA algorithms by first determining a number of images in T for which the first score SD( ) is less than the second score SD( ), and then dividing said number of images by n.
18. The process of claim 17 , wherein, whenever the semantic RCS is greater than 0.5 the annotation precision of AIA algorithm 1 is greater than that of AIA algorithm 2, whenever the semantic RCS is less than 0.5 the annotation precision of AIA algorithm 2 is greater than that of AIA algorithm 1, and whenever the semantic RCS is equal to 0.5 the annotation precision of AIA algorithms 1 and 2 is the same.