[open-bibliography] [Open-access] [open-science-dev] Fwd: [open-science] fw: Python NLTK/data mining/machine learning project of public research data, anyone interested?

[Mark MacGillivray]

On Tue, Sep 25, 2012 at 6:53 PM, Peter Murray-Rust <pm286 at cam.ac.uk> wrote:

> At OKFest we had a very successful hackathon looking at what we could
> extract from bibliographic data. Michael Bauer (copied) trawled the
> BioMedCentral site and has extracted a large amount of bibdata. We plan to
> put this in Bibserver.
>

He has already done so, which brought up some issues I am resolving as part
of a re-design anyway. Should be done next week.



> One idea that we want to do is create ids for each institution mentioned
> in the author list, based on the text, e.g.
>
> Unilever Centre, Dep. Of Chemistry
> University of Cambridge
> CB2 1EW, UK
>
> This would allow us to create facets for institutions, create a list and
> browse using Bibserver. (Although we cannot formally uniquify, this is a
> much easier problem than authors.
>

Actually we can facet without identifiers. It can be done directly on the
name string. Identifiers just provide us a way to connect different names
for the same thing, but the problem is still the same - we need to identify
that two things are the same in the first place.

Mark





> Laurent - I came across GROBID and am keen to re-use, rather than
> reinvent.
>
> Perhaps we should form an informal group in this technology and coordinate
> some of our efforts?
>
> P.
>
>
> --
> Peter Murray-Rust
> Reader in Molecular Informatics
> Unilever Centre, Dep. Of Chemistry
> University of Cambridge
> CB2 1EW, UK
> +44-1223-763069
>
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>
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