Calculates distance between articles and recommend new articles to read
- Teach some article url's to recko
- Calculates the distance between teached articles according to keywords extracted
- Then get closest neighbors of given articles
- brings recommendations according to user's liked articles
- copy the
config.py.copy
asconfig.py
- change inside according to your config details
- run app.py for flask web server
- run teacher.py for teaching articles
- run calculate.py for distance calculating worker
-
For teaching urls
GET /teach?url=<path-to-url>
-
For getting one of the closest neighbors of given url
GET /neighbor?url=<url-id>
-
Authenticate a new client
POST /authenticate {}
returns {token: <access token>}
-
Get a suggestion
GET /next?token=<access_token>
returns a response according to your likes
-
Like an article
POST /like?token=<access_token> {url: <article_id>}
- numpy
- scipy
- mongodb
- redis
- embedly account for extracting kw's