20. The non-transitory computer-readable storage medium of claim 16 , wherein the model is configured such that smaller topics are not submerged by larger topics.
16. A non-transitory computer-readable storage medium containing instructions, that when executed, control a computer system to be configured for: defining information for a set of genomes, the set of genomes describing characteristics of media programs; defining which genomes in the set of genomes correspond to which topics in a set of topics; inputting textual information for a plurality of media programs and the information for the set of genomes into a model; training the model to determine a probability distribution of terms for the set of topics based on analyzing the textual information and the information for the set of genomes, wherein training comprises incorporating a parameter that prevents topics from being submerged by other topics that are larger via a first item in the model; and outputting the trained model, wherein the probability distribution of terms is usable to determine genomes for each of the plurality of media programs, wherein a genome corresponds to a topic and is associated with a media program based on terms found in the textual information for the media program and the probability distribution of terms for the topic corresponding to the genome.