CODEWITHSUNDEEP
algorithmmongodbhadoopmahoutmahout-recommender
Abhimanyu
Abhimanyu

Reputation: 695

Mahout Content Based Recommendation Engine

I am working on a recommendation problem (Content based recommendation). I have my data set in mongodb in json format.

Problem Statement
There are items which have their own properties, and users have some preference regarding each properties. Now I am thinking to predict how much the item x will be liked by the user based on the properties of item and comparing the preferences of the user for same properties that item x have. I want to build a recommendation system to recommend the items to user , based on their preference.

I am thinking of using Mahout and CBAYES Classifier algorithm to predict , "how much item x will be liked by User A ". But I haven't found any example and data set for implementing CBAYES using mahout.

If you have any other suggestion to use any other classifier algorithm then please recommend.

Upvotes: 2

Views: 567

Answers (1)

Raja sekar
Raja sekar

Reputation: 73

You can calculate “how much item x will be liked by User A” by using cosine similarity. Please refer the following link for your more information.

Reference link: What's difference between Collaborative Filtering Item-based recommendation and Content-based recommendation

Regards,

Rajasekar

Upvotes: 1

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