cf_recommender 0.0.7

Real Time Recommendation System of Collaborative Filtering

It is a collaborative filtering type RealTime recommendation engine of open source that has been implemented in Python. The Amazon provides a “Customers who bought this product Customers who bought this product also purchased” function and, function similar to the “recommended users” feature of Twitter.

Features

• get fast within 10ms

• Real time updating recommendation list

• easy install

• High versatility

• Tags Support

Installation

$ pip install cf_recommender

Sample Code

# -*- coding: utf-8 -*-
from __future__ import absolute_import, unicode_literals
from cf_recommender.recommender import Recommender

cf_settings = {
    # redis
    'expire': 3600 * 24 * 30,
    'redis': {
        'host': 'localhost',
        'port': 6379,
        'db': 0
    },
    # recommendation engine settings
    'recommendation_count': 10,
    'recommendation': {
        'update_interval_sec': 600,
        'search_depth': 100,
        'max_history': 1000,
    },
}


# Get recommendation list
item_id = 'Item1'
recommendation = Recommender(cf_settings)
print recommendation.get(item_id, count=3)
>>> ['Item10', 'Item3', 'Item2']

# register history
user_id = 'user-00001'
buy_items = ['Item10', 'Item10', 'Item10', 'Item3', 'Item3', 'Item1']
for item_id in buy_items:
    recommendation.register(item_id)
recommendation.like(user_id, buy_items)


...

Bench Mark

License

License :: Free For Home Use

For companies and organizations

Commercial License

Commercial Licenses are available to legal entities, including companies and organizations (both for-profit and non-profit), which require the software for general commercial use.

• Free untill Dec 1, 2015

• $1000 used for each product From Dec 1, 2015

For individual developers

Always Free

Documentation

• get GoogleAPI token

• White Paper in Qiita