SaaS Recommendation Engine

Question

I'm looking for a recommendation engine for a media company.

this engine should deliver recommendations on website and native mobile-apps.

it should handle news articles, classifieds products, web-shop products, entries from listing portals.

following methods should be possible:

• contextual recommendations (keywords matching)
• trending articles/products in specific periods
• collaborative filtering
• behavioral recommendations (based on the userflow on all websites, where the engine is running. e.g. user reads many chevrolet-articles, then it should get recommendations from a classified portal with chevrolets)

it would also good, if this this recommendations are filterable on categories, dates, geo-data or something else data (provided in meta tags on the websites) e.g. "give me only recommendations with articles published since yesterday --> articles with meta tag <meta name="rec-date" content="2013-10-10" />"

Do anybody know some Recommendation Engine like this? I found only something like cxense.com... any alternatives?

Answer 1

There is the Google Prediction Api: https://developers.google.com/prediction/ It's a pretty flexible machine learning tool, where you could build what you need yourself.

Answer 2

YooChoose SaaS recommendation engine: http://www.yoochoose.com/en/our-product/yoochoose-newsmedia/

Answer 3

Considering your requirements, Recombee (https://www.recombee.com) could be a good fit. It supports both the collaborative filtering and text-mining/content-based recommendation. It also has very good support for filtering through its filtering/boosting language, ReQL (https://docs.recombee.com/reql.html). You may freely define custom set of item properties to be used for both learning a filtering, and there are even native functions such as earth_distance for your geo-restrictions.