Document Type
Conference Paper
Rights
This item is available under a Creative Commons License for non-commercial use only
Disciplines
Computer Sciences
Abstract
In this paper we present RaScAL, an active learning approach to predicting real-valued scores for items given access to an oracle and knowledge of the overall item-ranking. In an experiment on six different datasets, we find that RaScAL consistently outperforms the state-of-the-art. The RaScAL algorithm represents one step within a proposed overall system of preference elicitations of scores via pairwise comparisons.
Recommended Citation
O'Neill, Jack; Delany, Sarah Jane; and Namee, Brian Mac, "From Rankings to Ratings: Rank Scoring Via Active Learning" (2018). Conference papers. 265.
https://arrow.tudublin.ie/scschcomcon/265
Publication Details
This work will be published as part of the book "Emerging Topics in Semantic Technologies. ISWC 2018 Satellite Events. E. Demidova, A.J. Zaveri, E. Simperl (Eds.), ISBN: 978-3-89838-736-1, 2018, AKA Verlag Berlin"