CODEWITHSUNDEEP
c++textclassificationbayesian
Gilad Novik
Gilad Novik

Reputation: 4604

Bayesian classification or similar technique for recommendation system

I'm working on a news app. On the home page, the user sees a list of headlines and then he can click one to read the article and comment.

I would like to offer an option for "recommended articles" based on his history. For example, if he read an article - I'll feed the algorithm with the headline keywords so it will learn what this user likes to read.

My problem with what I've read about bayesian filters is that you need to train them with good input and bad input (such as good emails and spam emails). The difference in my case is that there are no bad examples. If the user didn't read an article - it doesn't mean it's a bad classification (since he still might read it in the future), but only if he read one - it's more likely that he'll read similar articles in the future.

Basically, I'm looking for an algorithm to help me recommend articles to a specific user - based on what he read in the past. It will run on a mobile device, so any implementation (C/C++/Obj-C) will work.

Thanks.

Upvotes: 0

Views: 786

Answers (1)

etr
etr

Reputation: 1262

You can treat this as a binary classification problem. It is either an article he likes to read or an article he possibly doesn't like to read.

You can use the dlib C++ library for the binary classifier algorithm.

Upvotes: 2

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