You have data about the following:
Users
Movies
User ratings of the movies
You need to predict whether a user will like a particular movie.
Which Matchbox recommender should you use?
A.
Item Recommendation
B.
Related Items
C.
Rating Prediction
D.
Related Users
Explanation:
https://msdn.microsoft.com/en-us/library/azure/dn905970.aspx#RatingPredictionOptions
Match Box Recommender:
– Need to have dataset of format- User-Item- Rating Triples
Score Matchbox recommender:
– It supports different types of recommendations
○ Predict ratings
When you predict ratings, the model calculates how a given user will react to a particular item, given the training data. Therefore, the input data for scoring must provide both a user and the item to rate.
From
○ Recommended Items
the model uses its knowledge about existing items and users to generate a list of items with probable appeal to each user. You can customize the number of recommendations returned, and set a threshold for the number of previous recommendations that are required in order to generate a recommendation.
From
○ Find related users
option to find related users is useful if you are recommending “people like you”, or if you are creating a pool of similar users on which to base other types of predictions
From
○ Find related items
predicting related items, you can generate recommendations for users based on items that have already been rated.
From
1
0