tree: 51774643ba9991759b4f15693edced9ee5851a19 [path history] [tgz]
  1. data/
  2. project/
  3. src/
  4. .gitignore
  5. build.sbt
  6. engine.json
  7. README.md
examples/experimental/scala-parallel-recommendation-cat/README.md

Recommendation Template support categories filtering

Documentation

The data requirement is similar to “Similar Product Template”. Please see. http://predictionio.incubator.apache.org/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.

Development Notes

import sample data

$ python data/import_eventserver.py --access_key <your_access_key>

query

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}