Since PIO has moved to Apache, the namespace of PIO code changed and so all templates need to be updated. None of the ones in https://github.com/PredictionIO/ <https://github.com/PredictionIO/template-scala-parallel-universal-recommendation> will work with Apache PIO. For the upgraded UR see: https://github.com/actionml/universal-recommender Docs for the UR are here: http://actionml.com/docs/ur <http://actionml.com/docs/ur>
Also look on the Template gallery page here for a description of template status. Some have not been moved to the new namespace and converted to run with PIO but this is pretty easy to do yourself. http://predictionio.incubator.apache.org/gallery/template-gallery/ <http://predictionio.incubator.apache.org/gallery/template-gallery/> user_id, product_id and purchase_date is all you need to use any recommender. If you plan to gather other events in the future, use the UR. As far as item or user based recommendations, the UR will give either based on the query with the same data and model, as some others will do. The UR allows you to mix both types in a single query, which may be useful with small amounts of individual user data. Also the accepted wisdom about this it to put item-based recs on item detail pages, and user-based recs elsewhere, when you don’t have an item to base recs on, or in another placement on any page. You can have many different placements of recs in any page by changing the queries. This is how Netflix gets rows and rows of specialized recs for different things all based on the same data. The UR queries are quite flexible. On Mar 23, 2017, at 7:08 AM, Vaghawan Ojha <[email protected]> wrote: Hi, I've been trying to deploy a recommendation system using https://github.com/PredictionIO/template-scala-parallel-universal-recommendation <https://github.com/PredictionIO/template-scala-parallel-universal-recommendation>. I've purchase history of user something like this: user_id, product_id and purchase_date, so I will be using user_id and product_id to determine the recommendation. I'm not sure if I would be able to customize the default even parameter. Do you have any suggestions like which template would be more suitable for my problem. I don't have data like rating or view state, I only have data about user and product they purchased. I need something like item based similarity as well as user based item similarity. Any help would be great Thank you Vaghawan
