Talk:Data mining
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Very wierd --- long introduction, then a table of contents, followed by brief history, some links and some references.
I didn't find this entry academic enough, there aren't enough examples of theory, applications and methods, it mostly talks about the dangers of data mining as if it is a dangerous thing. Needs content. --Exa 15:53, 20 Apr 2004 (UTC)
I've removed the Motley Fool Foolish Four reference as an example of retrospective data mining. Funnily enough, I worked at the Motley Fool at the time -- the UK site -- and the statement as it stood was factually incorrect.
Without wanting to digress too wildly: the Foolish Four was abandoned because at a time of rather huge gains with practically every other investment strategy (this was when the FTSE 100 had recently hit 7,000 and the Dow 11,000) it was showing a small loss and this was considered embarrassing. Had it in fact been continued it would likely have outperformed most other strategies (and indeed the market) over the next year or so at least.
It's true that data mining is a particular danger with such "mechanical" investing strategies and I've tried to reflect that in the paragraph I've inserted. Mswake 22:43, 26 Feb 2004 (UTC)
Data mining is becoming more than just conventional processing; apparently it is now expanding into other fields including multimedia data mining. However, I'm not sure as whether extended data mining styles/methods can be covered in the data mining article or should be covered in another article?
I added a simple example of what data mining offers (8:13 EST 21 Nov. 2004)
Except for maybe some very specific subfields, data mining seems to be managementspeak-ish. I mean in most cases where the work is used, looks like it is just a synonym for scientific method in its full generality. Discovering human-useful strategies from oracles in combinatorial games (e.g. from endgame tablebases for chess) [See the addition I've made in the page] is called data-mining, when it is called anything at all. (I published a paper once, in the early days of this thing - it was at first rejected, but when I resubmitted it with the only change being the title - I inserted the magic term "data mining" in the title, and the same journal promptly published it.)
The article reads well as an introduction to Data Mining, until the line mentioning the A Priori algorithm, at which point the technical level of the article shoots up and the reader is bombarded with terminology unfamiliar to anyone without a mathematical background. For example, no explanation of an oracle is given (the linked article deals with ancient mythological beings) and the writer makes many other assumptions about the reader's level of knowledge. Perhaps this paragraph could be put as a separate "technical details" section, or at least be re-written in a less dense (no pun) more patient manner.
As a newcomer to the field, I found the article very lightweight. Some of the better introductions to the topic are available in the links that are cited.