arnaucube
/
goRecommender
mirror of https://github.com/arnaucube/goRecommender.git
1
0
Fork 0
Code Issues Projects Releases Wiki Activity
You can not select more than 25 topics Topics must start with a letter or number, can include dashes ('-') and can be up to 35 characters long.
3 Commits
1 Branch
0 Tags
40 KiB
 
 
Tree: b403a740cf
Branches Tags
${ item.name }
Create branch ${ searchTerm }
from 'b403a740cf'
${ noResults }
arnaucode b403a740cf added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
.gitignore Initial commit 6 years ago
LICENSE Initial commit 6 years ago
README.md added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
errors.go server structure, mongodb connection 6 years ago
itemSamples.data added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
main.go added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
mongodb.go added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
mongodbConfig.json added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
mongodbModels.go added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
readItemSamples.go added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
serverConfig.go server structure, mongodb connection 6 years ago
serverConfig.json server structure, mongodb connection 6 years ago
serverRoutes.go added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago
tests.sh added initial items, implemented route newUser, starting recommendations, added tests.sh file 6 years ago

README.md

goRecommender

Recommendation system API, based on Machine Learning, written in Go lang

Data stored in MongoDB

Applies Machine Learning to perform recommendations:

  • Random Forests
  • K Nearest Neighbours

Documentation

  • Add new user
POST /user
{
    id: "user1",
    age: 30
}
  • Get recommendations
GET /r/{userid}/{nrec}

{userid}: is the userid
{nrec}: number of recommendations requested