: Faceting on manufacturers and categories first and than present the
: corresponding facets might be used under some circumstances, but in my case
: the category structure is quite deep, detailed and complex. So when
: the user enters a query I like to say to him "Look, here are the
: manufacturers and categories with matches to your query, choose one if you
: want, but maybe there is another one with products that better fit your
: needs or products that you didn't even know about. So maybe you like to
: filter based on the following attributes." Something like this ;o)
categories was just an example i used because it tends to be a common use
case ... my point is the decision about which facet qualifies for the
"maybe there is another one with products that better fit your needs" part
of the response either requires computing counts for *every* facet
constraint and then looking at them to see which ones provide good
distribution, or by knowing something more about your metadata (ie: having
stats that show the majority of people who search on the word "canon" want
to facet on "megapixels") .. this is where custom biz logic comes in,
becuase in a lot of situations computing counts for every possible facet
may not be practical (even if the syntax to request it was easier)
I get your point, but how to know where additional metadata is of value
if not
just trying? Currently I start with a generic approach to see what
really is
in the product data, to get an overview of the quality of the data and
what happens if I use the data in the new search solution. Then I can
decide
what is to do to optimize the system, i.e. try to reduce the count of
attributes, get the marketing to split somewhat generic attributes into
more
detailed ones, find a way to display the most relevant facets for the
current
query first and so on...
Tom
