Lucas,
Probably one of the solution will be to use database - like my sql and
setup Lucene against MySQL - in thi scase you don't need to think less
concerning implementaiton based on the content sotrage. ALso you need to
create middle tier to catch all event concerning Users Search / Hostory/
Retrieval History/Cache Management...
Thanks,
dt
www.ejinz.com
Search News
----- Original Message -----
From: "Lukas Vlcek" <[EMAIL PROTECTED]>
To: <java-user@lucene.apache.org>
Sent: Friday, August 10, 2007 2:28 AM
Subject: How to keep user search history and how to turn it into
information?
Hi,
I would like to keep user search history data and I am looking for some
ideas/advices/recommendations. In general I would like to talk about
methods
of storing such data, its structure and how to turn it into valuable
information.
As for the structure:
==============
For now I don't have exact idea about what kind of information I should
keep. I know that this is application specific but I believe there can be
some common general patterns. as of now I think can be useful to keep is
the
following:
1) system time (time of issuing the query) and userid
2) original user query in raw form (untokenized)
3) expanded user query (both tokenized and untokenized can be useful)
4) query execution time
5) # of objects retrieved from index
6) # of total object count in index (this can change during time)
7) and possibly if user clicked some result and if so then which one (the
hit number) and system time
As for the information I can get from this:
=============================
Such minimal data collection could show if the search engine serves users
well or not (generally said). I should note that for the users in this
case
the only other option is to not use the search engine at all (so the data
should not be biased by the fact that users are using alternative search
method). I should be able to learn if:
1) there are bottleneck queries (Prefix,Fuzzy,Proximity queries...)
2) users are finding what they want (they can find it fast and results are
ordered by properly defined relevance [my model is well tuned in terms of
term weights] so the result they click is among first hits)
3) user can formulate queries well (do they issue queries which return all
index documents or they can issue queries which return just a couple of
documents)
4) ...?... etc...
As for the storage method:
===================
I was planning to keep such data in database but now it seems to me that
it
will be better to keep it directly in index (Lucene index). It seems to me
that this approach would allow me for better fuzzy searches across history
and extracting relevant objects and their count more efficiently (with
benefit of the relevance based search on top of history search corpus).
I think that more scalable solution would be to keep such data in pure
flat
file and then periodically recreate search history index (or more indices)
from it (for example by Map-Reduce like task). Event better the flat file
could be stored in distributer file system. However, for now I would like
to
start with something simple.
I know this is a complex topic...
Regards,
Lukas
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