1. In a computing environment, a computer-implemented method performed on at least one processor, comprising: creating a similarity measure between objects, each object represented by term vectors, including learning values of the term vectors by: extracting terms from each object for generating a plurality of features from each of the extracted terms; for each of the extracted terms, creating a term vector by including one or more of the plurality of features, the one or more of the plurality of features of the term vector being associated with one or more model parameters; creating a term-weighting function including the term vectors associated with the extracted terms; learning the one or more model parameters of the term vectors of the term-weighting function that optimize a loss function to construct a learned term-weighting function; and applying the learned term-weighting function to determine similarity between the objects.