anchor.diff:  {"itemScores":[{"item":"i12","score":1.1700499715209998},{"item":"i21","score":1.1153550716504106},{"item":"i43","score":1.1153550716504106},{"item":"i14","score":1.0773502691896257},{"item":"i39","score":1.0773502691896257},{"item":"i26","score":1.0773502691896257},{"item":"i44","score":1.0773502691896257},{"item":"i38","score":0.9553418012614798},{"item":"i36","score":0.9106836025229592},{"item":"i46","score":0.9106836025229592}]}
   ```
   
  -Only recommend items with selected categories:
  +In addition, the Query support the following optional parmaters `categories`, `whiteList` and `blackList`.
  +
  +Recommend items with selected categories:
   
   ```
   curl -H "Content-Type: application/json" \
   -d '{
     "items": ["i1", "i3"],
  -  "num": 10, "categories" : ["c4", "c3"]
  +  "num": 10,
  +  "categories" : ["c4", "c3"]
   }' \
   http://localhost:8000/queries.json
   
   {"itemScores":[{"item":"i21","score":1.1153550716504106},{"item":"i14","score":1.0773502691896257},{"item":"i26","score":1.0773502691896257},{"item":"i39","score":1.0773502691896257},{"item":"i44","score":1.0773502691896257},{"item":"i45","score":0.7886751345948129},{"item":"i47","score":0.7618016810571367},{"item":"i9","score":0.7618016810571367},{"item":"i28","score":0.7618016810571367},{"item":"i6","score":0.7618016810571367}]}
   ```
   
  -Only recommend items in the whiteList:
  +Recommend items in the whiteList:
   
   ```
   curl -H "Content-Type: application/json" \
   -d '{
     "items": ["i1", "i3"],
  -  "num": 10, "categories" : ["c4", "c3"],
  +  "num": 10,
  +  "categories" : ["c4", "c3"],
     "whiteList": ["i21", "i26", "i40"]
   }' \
   http://localhost:8000/queries.json
  
positive.code: - item's categories
  
  
  ## Sample Data for Quick Start
  
  For demonstration purpose, a python script is provided to import sample data for quick start. It imports 10 users (with user ID "u1" to "u10") and 50 items (with item ID "i1" to "i50") with some random assigned categories ( with categories "c1" to "c6"). Each user then randomly view 10 items.
  
  First, make sure you are under the `MySimilar` directory. Execute the following to import the data (Replace the value of access_key parameter by your **Access Key**):
  
  
negative.code: 
  ## Advanced Query
  
  Recommend items which are similar to multiple items:
  
  ```
  curl -H "Content-Type: application/json" \
  