10. A system as claim 9 recites, the operations further comprising: receiving a second new multimedia data item associated with a first label of the plurality of labels; extracting a third set of features from the second new multimedia data item; applying the classifier to the third set of features; based at least in part on applying the classifier to the third set of features, determining new similarity values corresponding to each of the individual labels; determining that the second new multimedia data item is one of the positive multimedia data items; determining that the classifier classified the second new multimedia data item as being associated with a second label of the plurality of labels, the second label being different from the first label; and adjusting at least two of the individual model vectors.
10. A system as claim 9 recites, the operations further comprising: receiving a second new multimedia data item associated with a first label of the plurality of labels; extracting a third set of features from the second new multimedia data item; applying the classifier to the third set of features; based at least in part on applying the classifier to the third set of features, determining new similarity values corresponding to each of the individual labels; determining that the second new multimedia data item is one of the positive multimedia data items; determining that the classifier classified the second new multimedia data item as being associated with a second label of the plurality of labels, the second label being different from the first label; and adjusting at least two of the individual model vectors. 12. A system as claim 10 recites, the operations further comprising updating the statistics based at least in part on determining the new similarity values.