Marc G. Fournier wrote:
> On Thu, 13 May 2010, Alvaro Herrera wrote:
>
>> Excerpts from Yeb Havinga's message of jue may 13 15:06:53 -0400 2010:
>>
>>> My $0.02 - I like the whole 'don't sort, search' (or how did they call
>>> it?) just let the inbox fill up, google is fast enough. What would be
>>> really interesting is to have some extra 'tags/headers' added to the
>>> emails (document classification with e.g. self organizing map/kohonen),
>>> so my local filters could make labels based on that, instead of perhaps
>>> badly spelled keywords in subjects or message body.
>
> I missed this when I read it the first time .. all list email does
> have an X-Mailing-List header added so that you can label based on
> list itself ... is that what you mean, or are you thinking of
> something else entirely?
Something else: if automatic classification of articles was in place,
there would be need of fewer mailing lists, depending on the quality of
the classification.
IMHO the problem of handling the big volume of the lists is not solved
by splitting into more, since it does not decrease the amount of posts
that are interesting from the subscribers perspective. It would only
mean that posters are more likely to make mistakes, a possible increase
in crossposts or 'my question was not answered there so now I try here'
on the sender part, and at the subscriber side bigger chance to miss
interesting articles. That my current mailing list setup works for me
supports this claim; I did not subscribe to less lists, but managed to
decrease the ms spent at 'handling' to an amount that became workable.
Though I do not believe algorithmic article classification/ranking to
provide a 100% fool proof filter, it might help decreasing the "ms spent
per article" more. Take a look at how "carrot2" clusters results from
the query "postgresql prepared transactions site:postgresql.org" -
http://search.carrot2.org/stable/search?source=web&view=tree&skin=fancy-compact&query=postgresql+prepared+transactions+site%3Apostgresql.org&results=100&algorithm=lingo&EToolsDocumentSource.country=ALL&EToolsDocumentSource.language=ENGLISH&EToolsDocumentSource.safeSearch=false
I wonder if a cluster algorithm could tag articles with (multiple)
keywords, e.g. 'hackers','prepared transaction','dba' etc etc. I could
then make filters or ranking on: hackers AND optimizer -> +10.
regards,
Yeb Havinga
