TU Darmstadt / ULB / TUbiblio

A Comprehensive Reference Model for Personalized Recommender Systems

Breyer, Matthias and Nazemi, Kawa and Stab, Christian and Burkhardt, Dirk and Kuijper, Arjan (2011):
A Comprehensive Reference Model for Personalized Recommender Systems.
In: Lecture Notes in Computer Science (LNCS); 6771, Springer, Berlin, Heidelberg, New York, In: Human Interface and the Management of Information: Part I, pp. 528-537, DOI: 10.1007/978-3-642-21793-7₆₀,
[Conference or Workshop Item]

Abstract

Existing reference models for recommender systems are on an abstract level of detail or do not point out the processes and transitions of recommendation systems. However, this information is relevant for developers to design or improve recommendation systems. Even so, users need some background information of the calculation process to understand the process and accept or configure these systems proper. In this paper we present a comprehensive reference model for recommender systems which conjuncts the recommendation processes on an adequate level of detail. To achieve this, the processes of content-based and collaboration-based systems are merged and extended by the transitions and phases of hybrid systems. Furthermore, the algorithms which can be applied in the phases of the model are examined to identify the data flow between these phases. With our model those information of the recommendation calculation process can be identified, which encourages the traceability and thus the acceptance of recommendations.

Item Type: Conference or Workshop Item
Erschienen: 2011
Creators: Breyer, Matthias and Nazemi, Kawa and Stab, Christian and Burkhardt, Dirk and Kuijper, Arjan
Title: A Comprehensive Reference Model for Personalized Recommender Systems
Language: English
Abstract:

Existing reference models for recommender systems are on an abstract level of detail or do not point out the processes and transitions of recommendation systems. However, this information is relevant for developers to design or improve recommendation systems. Even so, users need some background information of the calculation process to understand the process and accept or configure these systems proper. In this paper we present a comprehensive reference model for recommender systems which conjuncts the recommendation processes on an adequate level of detail. To achieve this, the processes of content-based and collaboration-based systems are merged and extended by the transitions and phases of hybrid systems. Furthermore, the algorithms which can be applied in the phases of the model are examined to identify the data flow between these phases. With our model those information of the recommendation calculation process can be identified, which encourages the traceability and thus the acceptance of recommendations.

Series Name: Lecture Notes in Computer Science (LNCS); 6771
Publisher: Springer, Berlin, Heidelberg, New York
Uncontrolled Keywords: Business Field: Digital society, Business Field: Visual decision support, Research Area: Generalized digital documents, Recommender systems, Reference models, Recommendation calculation, Calculation information, Data flow
Divisions: 20 Department of Computer Science
20 Department of Computer Science > Interactive Graphics Systems
Event Title: Human Interface and the Management of Information: Part I
Date Deposited: 12 Nov 2018 11:16
DOI: 10.1007/978-3-642-21793-7₆₀
Export:
Suche nach Titel in: TUfind oder in Google
Send an inquiry Send an inquiry

Options (only for editors)
Show editorial Details Show editorial Details