There is nothing wrong with data mining, per se, but it isn't the same thing as mining content for information models.

On Fri, Aug 29, 2014 at 11:42 AM, Patrik Eklund <peklund@xxxxxxxxx> wrote:

On 2014年08月29日 20:47, Peter Yim wrote:
> ...
> http://bits.blogs.nytimes.com/2014/08/27/looking-to-the-future-of-data-science/

> ... The “big” in big data tends to get all the attention, Mr. Etzioni
> said, ... involves both grammar and background knowledge.
> And the latter is something humans acquire through experience of the
> world.

Being new to this forum I may hit an "out of bounds", but my I7 tells me
"big data" should not even be about that "big". Size doesn't matter.
It's the complexity of data, and it's not even that. It's the complexity
of the structure of the data, like it's all about the complexity of the
anatomy of the swing, not just the complexity of the swing. A "big
swing" mostly brings you out of bounds, in particular when you focus on
that "big". Or at least, it produces a huge slice.

Data "mining" is really silly, if you ask me, and I for one think we
should reserve "mining" just for minerals, not for knowledge.

It's all about what logic really is, and isn't, isn't it?

Cheers,

Patrik



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