Publication
Title
Interactive evaluation of recommender systems with SNIPER: an episode mining approach
Author
Abstract
Recommender systems are typically evaluated using either offline methods, online methods, or through user studies. In this paper we take an episode mining approach to analysing recommender system data and we demonstrate how we can use SNIPER, a tool for interactive pattern mining, to analyse and understand the behaviour of recommender systems. We describe the required data format, and present a useful scenario of how a user can interact with the system to answer questions about the quality of recommendations.
Language
English
Source (book)
Proceedings of the 13th ACM Conference on Recommender Systems (RecSys '19), September 16-20, 2019, Copenhagen, Denmark
Publication
New york : Assoc computing machinery , 2019
ISBN
978-1-4503-6243-6
DOI
10.1145/3298689.3346965
Volume/pages
(2019) , p. 538-539
ISI
000557263400093
Full text (Publisher's DOI)
Full text (open access)
UAntwerpen
Faculty/Department
Research group
Project info
City of Things
Publication type
Subject
Affiliation
Publications with a UAntwerp address
External links
Web of Science
Record
Identifier
Creation 03.10.2019
Last edited 02.10.2024
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