1. A method for facilitating semantic event classification of a group of image records related to an event, the method comprising: extracting a plurality of visual features from each of the image records; generating a plurality of concept scores for each of the image records using the visual features, wherein each concept score corresponds to a visual concept and each concept score is indicative of a probability that the image record includes the visual concept; producing a codebook of semantic events by determining a pairwise similarity between pairs of data points corresponding to training events and applying spectral clustering to group the data points into different clusters with each cluster corresponding to one code word, based on the determined pairwise similarities; mapping the training events to the codebook to generate a Bag-of-Features (BOF) feature vector corresponding to each training event; training an event classifier based on the BOF features vectors corresponding to the training events; generating a feature vector corresponding to the event based on the concept scores of the image records; i) wherein the generation of the feature vector includes calculating a pairwise similarity between the concept scores of the image records and concept scores for predetermined training data points to generate individual feature vectors for each of the image records; and ii) mapping the individual feature vectors to the codebook of semantic events; and supplying the feature vector to the event classifier that identifies at least one semantic event.