Most tagging systems allow the creation of "tag clouds" based on the number of articles that use that tag. However, we could provide some other criteria for weighting tag importance. Naturally, this should carry over to searching and finding information in general. One additional weight factor would be the number of clicks on a particular tag - popularity among Users, not necessarily Content Creators. This also opens up possibilities for trend tracking that normal tag systems don't currently support (to my very limited knowledge). A time factor would be useful here - popularity over all time, over the last 6 months, last week, etc. Hard-coded time limits would likely be necessary for efficiency reasons, but it would still be very useful for a variety of applications. Another would be ranking based on importance to the User. For instance, if "programming" is an important topic to me, then in a user control panel page, I could put that as a tag to weight more heavily. We can give this real power, though, by also making the system also add weight to related tags, as determined by links and soforth. For instance, we could add weight to "C#" and "design patterns" because of their links with "programming." I'm currently unsure how to make these determinations, or how to (as the main TIME page describes) differentiate between "programming my DVR" and "writing computer programs," but such a system would be especially powerful.
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