Understanding item consumption orders for right-order next-item recommendation

作者：Chen, Jun; Wang, Xuecheng; Wang, Chaokun^*

来源：Knowledge and Information Systems, 2018, 57(1): 55-78.

DOI：10.1007/s10115-017-1122-5

• Right-order recommendation
• IPat graph
• Item consumption order

Although the relevance problem in recommender systems, which typically refers to the similarity between the preference of the user and the items the system recommends, has been well studied, the issue of making recommendations in right orders has barely been mentioned before. The order defines the way in which items should be better consumed in relation to each other. The analysis of real-world data sets demonstrates strong item consumption patterns in the degree of order. In this paper, we propose a novel method to tackle the right-order recommendation problem based on a graph structure that incorporates the item consumption orders. The proposed method can combine relevance and order effects in recommendations. We attempt to recommend the relevant items in the consecutive steps within a user session so that the user's selected items in the consecutive steps can be stringed together in a right order. The experimental evaluation conducted on three real-world data sets shows that the recommendation accuracy is improved by considering item consumption orders compared with the baseline recommendation methods. In addition, the study on right-order recommendation contributes to the exploration on recommendation appropriateness besides relevance.

• 出版日期2018-10
• 单位清华大学