Michael, very good point. thank you
David, I am simply asking from a general perspective, in a recommendations
based system, how does escape from the feedback loop that is generated from
a successful recommendations engine suggesting clothes, then those clothes
get purchased more, then the recom
Also the data the recommendation is based on is not static and not only relying
on the recommendations.
So there are people buying, liking etc. new products come in some are promoted,
there are hypes etc.
Lots of variables that affect the data that is fed into the recommendation, and
then peop
Javad,
The graph database would probably just store the list of things you could
choose amongst for your recommendations; a graph database doesn't do
recommendations, and hence whether or not those recommendations would
reenforce one another would depend on the kind of algorithm you're using
f
