Efficient Weighted Association Rules Mining for Recommendation System

摘要

Association rules are often utilized in recommendation systems for the creation of suggested items lists, but all items in a basket database are treated uniformly. In this paper, we present an algorithm where the items are given weights to reflect their importance to the user. The weights may correspond to special promotions on some products, or the profitability of different items. Using weights, We can mine the weighted association rules to discover the nearest neighbor concerned items, then get the recommendation for the user by making use of the interest combined the confidence of rules.