A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews
|Title:||A Multi-Domain Analysis of Explanation-Based Recommendation using User-Generated Reviews||Authors:||Muhammad, Khalil
|Permanent link:||http://hdl.handle.net/10197/10126||Date:||23-May-2018||Online since:||2019-04-24T12:05:34Z||Abstract:||This paper extends recent work on the use of explanations in recommender systems. In particular, we show how explanations can be used to rank as well as justify recommendations, then we compare the results to more conventional recommendation approaches, in three large-scale application domains.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||AAAI Publications||Copyright (published version):||2018 Association for the Advancement of Artificial Intelligence||Keywords:||Explanations; Recommender systems; Artificial intelligence; Explanation-based recommendation||Other versions:||https://sites.google.com/site/flairs31conference/
|Language:||en||Status of Item:||Peer reviewed||Conference Details:||The Thirty-First International FLAIRS Conference (FLAIRS-31), Florida, United States of America, 21-23 May 2018|
|Appears in Collections:||Insight Research Collection|
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