[OPEN-ILS-GENERAL] Improving relevance ranking in Evergreen

Dan Scott dan at coffeecode.net
Sat May 12 18:00:39 EDT 2012


On Wed, Mar 7, 2012 at 10:11 AM, Mike Rylander <mrylander at gmail.com> wrote:
> On Wed, Mar 7, 2012 at 8:35 AM, Hardy, Elaine
> <ehardy at georgialibraries.org> wrote:
>> Kathy,
>>
>> While the relevance display is much improved in 2.x, it would be good to
>> have greater relevance given, in a keyword search, to title (specifically
>> the 245)and then subject fields. I also see where having a popularity
>> ranking might be beneficial.
>>
>> I just had to explain to a board member of one of our libraries why his
>> search for John Sandford turned up children's titles first. So having MARC
>> field 100s ranked higher than 700 in author searches would be beneficial
>> as well.
>>
>
> To be clear, weighting hits that come from different index definitions
> has always been possible.  2.2 will have a staff client interface to
> make it easier, but the capability has been there all along.
>
> Weighting different parts of one indexed term -- say, weighting the
> title embedded in the keyword blob higher than the subjects embedded
> in the same blob -- would require the above-mentioned "make use of
> tsearch class weighting".  But one can approximate that today by
> duplicating the index definitions from, say, title, author and subject
> classes within the keyword class.

We've been doing the latter (duplicating "title" inside the keyword
class) since 1.6 days - see
http://coffeecode.net/archives/218-Adjusting-relevancy-rankings-in-Evergreen-1.6,-some-explorations.html
for a description of how I added a keyword|title field, and then
boosted its weight to 10 (versus the default of 1 that the rest of the
keyword fields get). So a general keyword search for "programming
languages" on our system by far prefers results that contain
"programming languages" in the title... this is still working nicely
in 2.1 for us.

Note, however, that we did clear all entries out of the
search.relevance_adjustment table as that was found to slow things
down massively in the 2.0 era.


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