Automatic Generation of Natural Language Explanations

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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.
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Detaljer

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.
OriginalsprogEngelsk
TitelProceedings of the 23rd International Conference on Intelligent User Interfaces
ForlagAssociation for Computing Machinery
Publikationsdato8 mar. 2018
Artikelnummer57
ISBN (Elektronisk)978-1-4503-5571-1
DOI
StatusUdgivet - 8 mar. 2018
PublikationsartForskning
Peer reviewJa
BegivenhedInternational Conference on Intelligent User Interfaces - Hitotsubashi Hall (National Center of Sciences Building), Tokyo, Japan
Varighed: 7 mar. 201811 mar. 2018
Konferencens nummer: 23
https://iui.acm.org/2018/

Konference

KonferenceInternational Conference on Intelligent User Interfaces
Nummer23
LokationHitotsubashi Hall (National Center of Sciences Building)
LandJapan
ByTokyo
Periode07/03/201811/03/2018
Internetadresse

Kort

ID: 273236173