The data requirement is similar to “Similar Product Template”. Please see. http://docs.prediction.io/templates/similarproduct/quickstart/
By default, view events and MLlib ALS trainImplicit is used.
The main difference is:
Query by user Id instead of list of item Ids.
$ python data/import_eventserver.py --access_key <your_access_key>
normal:
$ curl -H "Content-Type: application/json" \
-d '{
"user" : "u1",
"num" : 10 }' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
$ curl -H "Content-Type: application/json" \
-d '{
"user" : "u1",
"num": 10,
"categories" : ["c4", "c3"]
}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
curl -H "Content-Type: application/json" \
-d '{
"user" : "u1",
"num": 10,
"whiteList": ["i21", "i26", "i40"]
}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
curl -H "Content-Type: application/json" \
-d '{
"user" : "u1",
"num": 10,
"blackList": ["i21", "i26", "i40"]
}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}
unknown user:
curl -H "Content-Type: application/json" \
-d '{
"user" : "unk1",
"num": 10}' \
http://localhost:8000/queries.json \
-w %{time_connect}:%{time_starttransfer}:%{time_total}