1. A tag recommendation system comprising: a tag selection element operable to select a plurality of candidate media/tag pairs wherein a candidate tag of each of the candidate media/tag pairs exhibits raw co-occurrence with a target tag of a target media/tag pair; a tag co-occurrence normalization element operable to process each of the plurality of candidate media/tag pairs against the target media/tag pair resulting in corresponding tag co-occurrence (“TC”) relevance measures wherein the TC relevance measures are in a semantic domain; a visual language modeling element operable to generate a candidate visual language model (“VLM”) for each candidate tag of the plurality of candidate media/tag pairs and a target VLM for a target tag of the target media/tag pair, and further operable to process each of the candidate VLMs against the target VLM resulting in corresponding tag content correlation (“TCC”) relevance measures wherein such relevance measures are in a visual domain; a visual correlation element operable to process each of the candidate VLMs against the target VLM resulting in corresponding image-conditioned tag correlation (“ITC”) relevance measures wherein the ITC relevance measures are in a visual domain; and a multi-domain combining element operable to combine one or more TC tag lists indicated by the TC relevance measures with one or more TCC tag lists indicated by the TCC relevance measures and with one or more ITC tag lists indicated by the ITC relevance measures, and operable to form a list of recommended tags from the combined one or more TC tags and the one or more TCC tags and the one or more ITC tags.