Recommendation systems is application of Data Mining Technologies. I have researched about how to implement a recommendation system and as a part of my research, I studied recommendation systems that are already out there on the Internet and here are five examples of Recommendation systems on the web:

1. Amazon

Customers Who Bought This Item Also Bought:

Frequently Bought Together: (Example of Market Basket Analysis a.k.a Association Rules):

2. LinkedIn

You should read this: How does LinkedIn’s recommendation system work? – it would open up your brain to “recommendation” opportunities around you!

Jobs you may like + Groups you may like + Companies you may follow:

3. Netflix

Did you knew about Netflix Prize for improving their recommendation engine? If not you should read that!

Here’s their Movies you’ll love recommendation system:

4. Twitter

People you may want to follow:

5. Google

I do not have a screenshot but just wanted to point out the Google “personalize” (a.k.a recommends based on past behavior) search results based on your search history. And you can switch that off, if you want: Turn off search history personalization

Conclusion

In this blog-post, we saw examples of recommendation systems. The key take away is that there is more than one approach to building a recommendation system. The approaches can be based on 1. Past Behavior 2. Past Behavior of “friends” 3. Recommendation based on the Item that is being searched And you can definitely, Mix and Match!

And I hope this post helped you understand an application of data mining that’s all around us! And question: Where else do you see recommendation systems in action? Leave a comment!