TY - JOUR
T1 - Measuring the impact of online personalisation
T2 - Past, present and future
AU - Zanker, Markus
AU - Rook, Laurens
AU - Jannach, Dietmar
PY - 2019
Y1 - 2019
N2 - Research on understanding, developing and assessing personalisation systems is spread over multiple disciplines and builds on methodologies and findings from several different research fields and traditions, such as Artificial Intelligence (AI), Machine Learning (ML), Human–Computer Interaction (HCI), and User Modelling based on (applied) social and cognitive psychology. The fields of AI and ML primarily focus on the optimisation of personalisation applications, and concentrate on creating ever more accurate algorithmic decision makers and prediction models. In the fields of HCI and Information Systems, scholars are primarily interested in the phenomena around the use and interaction with personalisation systems, while Cognitive Science (partly) delivers the theoretical underpinnings for the observed effects. The aim and contribution of this work is to put together the pieces about the impact of personalisation and recommendation systems from these different backgrounds in order to formulate a research agenda and provide a perspective on future developments.
AB - Research on understanding, developing and assessing personalisation systems is spread over multiple disciplines and builds on methodologies and findings from several different research fields and traditions, such as Artificial Intelligence (AI), Machine Learning (ML), Human–Computer Interaction (HCI), and User Modelling based on (applied) social and cognitive psychology. The fields of AI and ML primarily focus on the optimisation of personalisation applications, and concentrate on creating ever more accurate algorithmic decision makers and prediction models. In the fields of HCI and Information Systems, scholars are primarily interested in the phenomena around the use and interaction with personalisation systems, while Cognitive Science (partly) delivers the theoretical underpinnings for the observed effects. The aim and contribution of this work is to put together the pieces about the impact of personalisation and recommendation systems from these different backgrounds in order to formulate a research agenda and provide a perspective on future developments.
KW - Adaptive systems
KW - Recommender systems
KW - Web personalisation
UR - http://www.scopus.com/inward/record.url?scp=85070959124&partnerID=8YFLogxK
U2 - 10.1016/j.ijhcs.2019.06.006
DO - 10.1016/j.ijhcs.2019.06.006
M3 - Article
AN - SCOPUS:85070959124
SN - 1071-5819
VL - 131
SP - 160
EP - 168
JO - International Journal of Human Computer Studies
JF - International Journal of Human Computer Studies
ER -