Automatic Generation of Natural Language Explanations
|Title:||Automatic Generation of Natural Language Explanations||Authors:||Costa, Felipe; Ouyang, Sixun; Dolog, Peter; Lawlor, Aonghus||Permanent link:||http://hdl.handle.net/10197/10860||Date:||11-Mar-2018||Online since:||2019-07-08T10:30:53Z||Abstract:||An interesting challenge for explainable recommender systems is to provide successful interpretation of recommendations using structured sentences. It is well known that user-generated reviews, have strong influence on the users’ decision. Recent techniques exploit user reviews to generate natural language explanations. In this paper, we propose a character-level attention-enhanced long short-term memory model to generate natural language explanations. We empirically evaluated this network using two real-world review datasets. The generated text present readable and similar to a real user’s writing, due to the ability of reproducing negation, misspellings, and domain-specific vocabulary.||Funding Details:||Science Foundation Ireland||Type of material:||Conference Publication||Publisher:||ACM||Copyright (published version):||2018 ACM||Keywords:||Recommender systems; Natural Language Generation; Explainability; Explanations; Neural Network||DOI:||10.1145/3180308.3180366||Other versions:||http://iui.acm.org/2018/||Language:||en||Status of Item:||Peer reviewed||Is part of:||IUI '18 Companion Proceedings of the 23rd International Conference on Intelligent User Interfaces Companion||Conference Details:||ACM IUI '18: 23rd International Conference on Intelligent User Interfaces Companion, Tokyo, Japan, 7-11 March 2018|
|Appears in Collections:||Insight Research Collection|
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