Journal ArticleDOI
A method for collaborative recommendation using knowledge integration tools and hierarchical structure of user profiles
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This paper proposes a new approach to collaborative profile recommendation using a hierarchical structure for user modeling in an information retrieval system a hierarchical user profile that is being recommended to a new user based on profiles of other, similar users.Abstract:
This paper proposes a new approach to collaborative profile recommendation using a hierarchical structure for user modeling. In an information retrieval system a hierarchical user profile, used to personalize the document retrieval process, is being recommended to a new user based on profiles of other, similar users. Using methodology from the Knowledge Integration domain, four criteria are defined and analyzed to complete the aim of recommendation: Reliability is required for maintaining the correct structure of the profile, O1 and O2 Optimality postulates are required to calculate the best output profile by minimizing distances to other profiles, and Conflict Solution is used to better represent situations inherent to profile recommendation. Based on those criteria, four algorithms are proposed: O1 and O2 algorithms and modified O1 and O2 algorithms. These algorithms are further analyzed to check if they provide good recommendation.read more
Citations
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References
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E-Commerce Recommendation Applications
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Proceedings Article
Combining collaborative filtering with personal agents for better recommendations
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