1. A method utilizing at least a computer processor for building a multimedia association graph comprising: collecting a set of multimedia documents; selecting at least one subset within the collected set of multimedia documents, the subset comprising at least one signal; creating a set of segments using a segmentation method, wherein the segmentation method segments the at least one signal into at least one level segment selected from a group consisting of: object level segments, attribute level segments and feature level segments; clustering the set of segments to create a cluster set, wherein the clustering comprises: computing a descriptor f for at least one signal segment in the set of segments; selecting a similarity measure for space of the descriptor f, wherein the selecting the similarity measure between two descriptors f1 and f2 is computed by the method comprising: mapping each coordinate of f1 to K>1 coordinates of f2; mapping each coordinate of f2 to K>1 coordinates of f1, where K indicates a number of coordinates; computing a penalty for each such coordinate mapping, wherein the penalty is computed such that closer coordinate mappings incur smaller penalties, additional penalties are incurred in response to a part of a particular coordinate that is left unmatched, a total penalty is computed as a sum of matched portions multiplied by their respective penalties plus any additional penalties for any unmatched portions; wherein a best matching is found to minimize the total penalty; and wherein the penalty for the best matching is declared as a value of the similarity measure; clubbing together signals with similar descriptors as per the similarity measure to obtain clusters of similar signals; building a dictionary of multimedia attributes, wherein each attribute corresponds to a cluster in the cluster set; building a dictionary of classifiers comprising at least one entry, wherein each entry classifies an attribute in the dictionary of multimedia attributes; and creating a graph wherein each node corresponds to an attribute in the multimedia attribute dictionary and a weight of edges or links indicates a degree of similarity between the attributes.