Title
A preference elicitation interface for collecting dense recommender datasets with rich user information.
Abstract
We present an interface that can be leveraged to quickly and effortlessly elicit people's preferences for visual stimuli, such as photographs, visual art and screensavers, along with rich side-information about its users. We plan to employ the new interface to collect dense recommender datasets that will complement existing sparse industry-scale datasets. The new interface and the collected datasets are intended to foster integration of research in recommender systems with research in social and behavioral sciences. For instance, we will use the datasets to assess the diversity of human preferences in different domains of visual experience. Further, using the datasets we will be able to measure crucial psychological effects, such as preference consistency, scale acuity and anchoring biases. Last, we the datasets will facilitate evaluation in counterfactual learning experiments.
Year
Venue
Field
2017
arXiv: Social and Information Networks
Recommender system,Data mining,Preference elicitation,Information retrieval,Computer science,Counterfactual thinking,User information,Behavioural sciences,Visual perception
DocType
Volume
Citations 
Journal
abs/1706.08184
0
PageRank 
References 
Authors
0.34
0
5
Name
Order
Citations
PageRank
Pantelis P Analytis1194.65
Tobias Schnabel22019.81
stefan m herzog332.07
Daniel Barkoczi401.69
Thorsten Joachims5173871254.06