Relevance and ranking in online dating systems pdf

28-Nov-2017 11:32

Simple approaches use the average values of the rated item vector while other sophisticated methods use machine learning techniques such as Bayesian Classifiers, cluster analysis, decision trees, and artificial neural networks in order to estimate the probability that the user is going to like the item.

To abstract the features of the items in the system, an item presentation algorithm is applied.A key issue with content-based filtering is whether the system is able to learn user preferences from users' actions regarding one content source and use them across other content types.