So there I was using CiteULike yesterday as I normally do when, maybe half an hour later, their UI was upgraded! What a pleasant surprise, because the tags feature upgrade has finally made it perfectly great to use.
Suppose you have already added an article into your CiteULike library and you went back to edit its metadata, there is a field for updating the tags for the article. It used to be that you had to blindly guess what tags you have previously used, as it didn't show such a list, which was a major impediment to using tags at all. As soon as you started using more than maybe ten tags, the entire tags system became unwieldy because of this.
Now, not only are the tags you've previously used listed, but auto-completion is also there. Further, when it shows a list of completion suggestions, it even lists along with each suggested tag the number of articles with that tag!
That makes me very happy. :)
I know, I know, the entire idea of using tags is actually rather problematic especially when the possible tags is not constrained by a defined vocabulary and so on. Sometimes it's a bit of a drag in terms of effort to have to tag anything at all (and I notice many CiteULike users use few or no tags). But that's the web 2.0 world we live in, where true semantic web-ness just doesn't exist because computers do not understand meaning.
Employing a system that automatically tags articles doesn't actually solve the problem entirely (and search engines are essentially an automated system that tags the articles showing up in your search with the "tags" that is the words in your search query). It doesn't actually solve the problem, no matter how good a machine learning system is at associating a set of sentences (in the form of an article) with a set of keywords or tags, because the system is still just associating or translating a set of symbols to another set of symbols without a clue what the symbols mean.
Oh well, that's why I'm doing the artificial intelligence research I'm doing now, because words have meaning.