TY - JOUR
T1 - The recommender canvas: A model for developing and documenting recommender system design
AU - van Capelleveen, Guido Cornelis
AU - Amrit, Chintan Amrit
AU - Yazan, Devrim Murat
AU - Zijm, Willem Hendrik Maria
PY - 2019/9/1
Y1 - 2019/9/1
N2 - The task of designing a recommender system is a complex process. Because of the many technological advancements that may be included in a recommender system, engineers are faced with a fast growing number of design related decisions to be taken. Unfortunately, there is no general approach yet for decision makers that can act as a framework guiding the design of a recommender system. The rich collection of literature on recommender systems, though, offers a great source to identify the key areas where these decisions need to be taken. In this paper, we survey existing literature with the aim of building a recommender system model inspired by Osterwalder’s canvas theory. The result of our semi-structured synthesis is a novel design approach in the form of a canvas for designing recommender systems. This work provides a better understanding and can serve as a guide for decision making in recommender system design.
AB - The task of designing a recommender system is a complex process. Because of the many technological advancements that may be included in a recommender system, engineers are faced with a fast growing number of design related decisions to be taken. Unfortunately, there is no general approach yet for decision makers that can act as a framework guiding the design of a recommender system. The rich collection of literature on recommender systems, though, offers a great source to identify the key areas where these decisions need to be taken. In this paper, we survey existing literature with the aim of building a recommender system model inspired by Osterwalder’s canvas theory. The result of our semi-structured synthesis is a novel design approach in the form of a canvas for designing recommender systems. This work provides a better understanding and can serve as a guide for decision making in recommender system design.
U2 - 10.1016/j.eswa.2019.04.001
DO - 10.1016/j.eswa.2019.04.001
M3 - Article
VL - 129
SP - 97
EP - 117
JO - Expert systems with applications
JF - Expert systems with applications
SN - 0957-4174
ER -