From Physical Agents to Recommender Agents

2003 ◽  
pp. 165-178 ◽  
Author(s):  
Josep Lluís de la Rosa ◽  
Esteve del Acebo ◽  
Beatriz López ◽  
Miquel Montaner
Keyword(s):  
Recommender Agents

scholarly journals Don’t Take it Personally: Resistance to Individually Targeted Recommendations with Anthropomorphic Recommender Systems

2020 ◽  
Author(s):  
Guy Laban ◽  
Theo Araujo
Keyword(s):  
Recommender Systems ◽  
Online Experiment ◽  
Recommender Agents

Recommender agents, artificially intelligent recommender systems that demonstrate anthropomorphic cues, are widely available online to provide consumers with individually tailored recommendations. Nevertheless, little is known about the effect of their anthropomorphic cues on users’ resistance to both the system and recommendations. Moreover, individually tailored recommendations require users to disclose information proactively or reactively for receiving customized or personalized recommendations, which can trigger users’ resistance to the platform and the recommendations. Accordingly, this study examined the extent to which recommender systems’ anthropomorphic cues and the type of recommendations provided (customized and personalized) influenced online users’ perceptions of control, trustworthiness, and the risk of using the platform. The study assessed how these perceptions, in turn, influence users’ adherence to the recommendations. An online experiment among online users (N = 266) with recommender agents and web recommender platforms that provided customized or personalized restaurant recommendations was conducted. The results of the experiment entail that when recommendations are customized, as compared to personalized, users are less likely to demonstrate resistance and are more likely to adhere to the recommendations provided. Furthermore, the study’s findings suggest that these effects are amplified for recommender agents, demonstrating anthropomorphic cues, in contrast to traditional systems as web recommender platforms.

Strategy recommender agents (ALEX) - the methodology

2007 ◽  
Author(s):  
Ronald Uriel Ruiz Ordóñez ◽  
Josep Lluis de la Rosa i Esteva ◽  
Javier Guzmán-Obando
Keyword(s):  
Recommender Agents

Integrating user modeling approaches into a framework for recommender agents

2010 ◽  
Vol 20 (1) ◽  
pp. 29-54 ◽  
Author(s):  
Daniela Godoy ◽  
Silvia Schiaffino ◽  
Analía Amandi
Keyword(s):  
User Modeling ◽  
Modeling Approaches ◽  
Recommender Agents

scholarly journals Assessing the impact of recommender agents on on-line consumer unplanned purchase behavior

2011 ◽  
Vol 48 (8) ◽  
pp. 336-343 ◽  
Author(s):  
R. Eric Hostler ◽  
Victoria Y. Yoon ◽  
Zhiling Guo ◽  
Tor Guimaraes ◽  
Guisseppi Forgionne
Keyword(s):  
Purchase Behavior ◽  
On Line ◽  
The Impact ◽  
Recommender Agents
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