If one were to enlist the benefits of Recommendation System in any business, the list would be endless. To give your users a very unique experience, it is imperative that you personalize your app for each and every user based on their behavior and interests. To help increase user engagement in your app, App42 Cloud APIs has a Recommendation Service that does not require you to code and learn the complicated algorithms. It provides recommendation based on customer ID, item ID and the preference of the customer for a particular item.
App42 Recommender Service gives you the option to provide user’s preference data in 2 ways:
Using File option, you just need to upload the file with the user’s preference data in CSV format. You can download the sample CSV file and update your user’s preference data and upload it.
Using Connector, you have the option to provide the preference data either from MongoDB or MySQL. You need to select the connector type and provide the required connection details like Host, User Name, Password, DB Name, and Table Name.
Once you have provided user’s preference data to App42, you can see it in App42 Management Console.
You can see the preferred items by a particular user and also by clicking on that, you can even see the item and its preference details.
Recommendations can be fetched based on user similarity and item similarity. This engine currently supports two types of algorithms i.e. EuclideanDistanceSimilarity & PearsonCorrelationSimilarity. By default when similarity is not specified, PearsonCorrelationSimilarity is used. For instance in the method ItemBased (Double userId, int howMany), it uses PearsonCorrelationSimilarity. In the method ItemBasedBySimilarity (String similarity, Double userId, int howMany) you can specify your choice of algorithm like Recommender.EUCLIDEAN_DISTANCE or Recommender.PEARSON_CORRELATION.
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