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From "Lukas Vlcek" <>
Subject How to keep user search history and how to turn it into information?
Date Fri, 10 Aug 2007 07:28:17 GMT

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

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

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
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...


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