Abstract: Examples are disclosed that relate to the automatic creation of playlists. For example, one disclosed example provides, on a computing device comprising a processor, a method for generating playlists of content items from a collection of content items. The method comprises determining a set of candidate playlists, where each candidate playlist may include a different plurality of content items selected from the collection of content items. The method further comprises assigning a score to each candidate playlist in the set, and presenting via a display a subset of candidate playlists. Each candidate playlist in the subset may be selected from the set of candidate playlists based on the assigned score of the candidate playlist.

Abstract: One or more multimedia recommendation candidates are identified for a user. For each of the one or more multimedia recommendation candidates, a similarity between a multimedia artist associated with that multimedia recommendation candidate and a preferred artist of the user is determined That multimedia recommendation candidate is recommended to the user if the similarity exceeds a threshold.

Abstract: A method and system for detecting abnormal events in a given environment comprises a model construction step comprising: a) a step of unsupervised initialization of Q groups; b) a step of definition of a model of normality consisting of 1-class SVM classifiers; c) a step of optimum distribution of the audio signals in the Q different groups; d) repetition of the steps b and c until a stop criterion C1, is checked and a model M is obtained; and a step of use of the model(s) M obtained from the construction step comprising the analysis of an unknown audio signal ST assigning a score to a 1-class SVM classifier, and a comparison of all the scores fq obtained using decision rules in order to determine the presence or absence of an anomaly in the audio signal analyzed.