Interactive evaluation of recommender systems with SNIPER
| Autor: | Sandy Moens, Olivier Jeunen, Bart Goethals |
|---|---|
| Rok vydání: | 2019 |
| Předmět: |
Computer. Automation
Information retrieval Economics Computer science media_common.quotation_subject 02 engineering and technology Recommender system 01 natural sciences User studies 010104 statistics & probability Episode mining Data format 020204 information systems 0202 electrical engineering electronic engineering information engineering Quality (business) 0101 mathematics Mathematics media_common |
| Zdroj: | RecSys Proceedings of the 13th ACM Conference on Recommender Systems (RecSys '19), September 16-20, 2019, Copenhagen, Denmark |
| DOI: | 10.1145/3298689.3346965 |
| Popis: | 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. |
| Databáze: | OpenAIRE |
| Externí odkaz: |
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