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Recently, electronic commerce (EC) websites have been unable to provide anidentification number (user ID) for each transaction data entry because ofprivacy issues. Because most recommendation methods assume that all data areassigned a user ID, they cannot be applied to the data without user IDs.Recently, session-based recommendation (SBR) based on session information,which is short-term behavioral information of users, has been studied. Ageneral SBR uses only information about the item of interest to make arecommendation (e.g., item ID for an EC site). Particularly in the case of ECsites, the data recorded include the name of the item being purchased, theprice of the item, the category hierarchy, and the gender and region of theuser. In this study, we define a pseudo--session for the purchase history dataof an EC site without user IDs and session IDs. Finally, we propose an SBR witha co-guided heterogeneous hypergraph and globalgraph network plus, calledCoHHGN+. The results show that our CoHHGN+ can recommend items with higherperformance than other methods.

Pseudo Session-Based Recommendation with Hierarchical Embedding and Session Attributes