On 09/03/2016 10:05, Robert Brown wrote:
Hi,
I'm looking for some advice and possible options for dealing with our
relevancy when searching through shopping products.
A search for "tablet" returns pills, when the user would expect
electronic devices.
Without any extra criteria (like category), how would/could you manage
this situation?
Any solution would also need to scale since this is just a random example.
Thanks,
Rob
Hi Rob,
Solr out of the box has no way of knowing that 'the user would expect
electronic devices', unfortunately: since the record for 'pills'
contains the word 'tablet', that's what you get. Note that if your users
were expecting a medical answer everything would be rosy!
Firstly, consider setting up some tests for these kinds of issues, so
you can measure if the adjustments you're making are having the effect
you want - we call this test-driven relevancy tuning. One tool you might
consider (if you don't want to use a pile of spreadsheets) is Quepid
(disclaimer: we resell this in the UK).
Then, you need to work out *why* the results are wrong for your use case
(using Solr's debugQuery helps here). If the words in the body text are
having a disproportionate effect, consider boosting another part of the
source data. Consider synonyms (if I search 'tablet' I should also get
'iPad'). To be honest this is a complex field with a lot of different
knobs to adjust - I would recommend you take a look at Doug Turnbull and
John Berryman's new book 'Relevant Search' (available on MEAP at Manning
Publications) which is an excellent take on this.
In short, you need a sensible methodology for tuning relevance,
otherwise it can easily become a game of whack-a-mole!
Cheers
Charlie
--
Charlie Hull
Flax - Open Source Enterprise Search
tel/fax: +44 (0)8700 118334
mobile: +44 (0)7767 825828
web: www.flax.co.uk
