One of the rarer types of articles in journals are the sort that seek to do a potted history of a discipline or sub discipline and while they may not make a new contribution to knowledge they are a great resource for people wanting to get up to speed with something.
A great example of such an article is Data Clustering: 50 Years Beyond K-Means by Anil K. Jain (pdf file) As K-means is still one of the most popular algorithms it just goes to show as with other areas of statistics that if your way of doing things arrives first and becomes commonly adopted it'll often trundle along even if better alternatives appear in the literature.
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