1. A method for building a catalog using visual objects, comprising: clustering a plurality of records, each record comprises at least one object image and at least one textual field associated with the object, to yield a plurality of clusters such that the object images in each cluster exhibit between them a visual similarity above a specified value; associating each cluster with a label by applying a dictionary function to the textual fields of each cluster, wherein the label reflects a common semantic factor of the textual fields of each cluster, wherein the common semantic factor has a value above a specified threshold, wherein the visual similarity provides a measure of resemblances between two visual objects that can be based on at least one of: the fit between their color distribution such as correlation between their HSV color histograms, the fit between their texture, the fit between their shapes, the correlation between this edge histograms, face similarity, methods that include local descriptors, the fit between their scaled gray level image such as matrix correlation or Euclidean distance, the fit between their segmented scaled objects of a gray level image, such as objects matrix correlation, the fit between their segmented scaled objects of an edge histogram, and the fit between their segmented scaled objects shape, wherein at least one of the clustering and the associating is executed by at least one processor.