1. A computer-implemented method for categorizing an object respective to at least two categorization dimensions, each categorization dimension being defined by a plurality of categories, the computer-implemented method comprising: determining a probability value indicative of the object for each category of each categorization dimension; and selecting a categorization label for the object respective to each categorization dimension based on (i) the determined probability values of the categories of that categorization dimension and (ii) the determined probability values of categories of at least one other of the at least two categorization dimensions; wherein the at least two categorization dimensions include first and second categorization dimensions, and the selecting of a categorization label respective to each categorization dimension includes: weighting the probability values of the categories of the first categorization dimension based on the probability values of the categories of the second categorization dimension to produce weighted probability values for the categories of the first categorization dimension; weighting the probability values of the categories of the second categorization dimension based on the probability values of the categories of the first categorization dimension to produce weighted probability values for the categories of the second categorization dimension; selecting the label respective to the first categorization dimension based on the weighted probability values for categories of the first categorization dimension; and selecting the label respective to the second categorization dimension based on the weighted probability values for categories of the second categorization dimension.