Real Time Recommendation System of Collaborative Filtering
Project description
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
Project details
Release history Release notifications | RSS feed
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