Effects of interactivity and presentation on review-based explanations for recommendations

User reviews have become an important source for recommending and explaining products or services. Particularly, providing explanations based on user reviews may improve users' perception of a recommender system (RS). However, little is known about how review-based explanations can be effectively and efficiently presented to users of RS. We investigate the potential of interactive explanations in review-based RS in the domain of hotels, and propose an explanation scheme inspired by dialog models and formal argument structures. Additionally, we also address the combined effect of interactivity and different presentation styles (i.e. using only text, a bar chart or a table), as well as the influence that different user characteristics might have on users' perception of the system and its explanations. To such effect, we implemented a review-based RS using a matrix factorization explanatory method, and conducted a user study. Our results show that providing more interactive explanations in review-based RS has a significant positive influence on the perception of explanation quality, effectiveness and trust in the system by users, and that user characteristics such as rational decision-making style and social awareness also have a significant influence on this perception.

READ FULL TEXT

page 1

page 2

page 3

page 4

research
06/09/2023

Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System

Explainable recommender systems (RS) have traditionally followed a one-s...
research
01/28/2022

Dynamic pricing and discounts by means of interactive presentation systems in stationary point of sales

The main purpose of this article was to create a model and simulate the ...
research
03/23/2018

Learning Recommendations While Influencing Interests

Personalized recommendation systems (RS) are extensively used in many se...
research
10/13/2020

Assessing the Helpfulness of Review Content for Explaining Recommendations

Despite the maturity already achieved by recommender systems algorithms,...
research
03/16/2023

Measuring the Impact of Explanation Bias: A Study of Natural Language Justifications for Recommender Systems

Despite the potential impact of explanations on decision making, there i...
research
08/02/2021

"Robot Steganography"?: Opportunities and Challenges

Robots are being designed to communicate with people in various public a...

Please sign up or login with your details

Forgot password? Click here to reset