The Problem of Coherence in Natural Language Explanations of Recommendations

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F23%3A10476181" target="_blank" >RIV/00216208:11320/23:10476181 - isvavai.cz</a>

Výsledek na webu

<a href="https://ebooks.iospress.nl/volumearticle/64414" target="_blank" >https://ebooks.iospress.nl/volumearticle/64414</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.3233/FAIA230482" target="_blank" >10.3233/FAIA230482</a>

Jazyk výsledku

angličtina

Název v původním jazyce

The Problem of Coherence in Natural Language Explanations of Recommendations

Popis výsledku v původním jazyce

Providing natural language explanations for recommendations is particularly useful from the perspective of a non-expert user. Although several methods for providing such explanations have recently been proposed, we argue that an important aspect of explanation quality has been overlooked in their experimental evaluation. Specifically, the coherence between generated text and predicted rating, which is a necessary condition for an explanation to be useful, is not properly captured by currently used evaluation measures. In this paper, we highlight the issue of explanation and prediction coherence by 1) presenting results from a manual verification of explanations generated by one of the state-of-the-art approaches 2) proposing a method of automatic coherence evaluation 3) introducing a new transformer-based method that aims to produce more coherent explanations than the state-of-the-art approaches 4) performing an experimental evaluation which demonstrates that this method significantly improves the explanation coherence without affecting the other aspects of recommendation performance.

Název v anglickém jazyce

The Problem of Coherence in Natural Language Explanations of Recommendations

Popis výsledku anglicky

Providing natural language explanations for recommendations is particularly useful from the perspective of a non-expert user. Although several methods for providing such explanations have recently been proposed, we argue that an important aspect of explanation quality has been overlooked in their experimental evaluation. Specifically, the coherence between generated text and predicted rating, which is a necessary condition for an explanation to be useful, is not properly captured by currently used evaluation measures. In this paper, we highlight the issue of explanation and prediction coherence by 1) presenting results from a manual verification of explanations generated by one of the state-of-the-art approaches 2) proposing a method of automatic coherence evaluation 3) introducing a new transformer-based method that aims to produce more coherent explanations than the state-of-the-art approaches 4) performing an experimental evaluation which demonstrates that this method significantly improves the explanation coherence without affecting the other aspects of recommendation performance.

Druh

D - Stať ve sborníku

CEP obor

—

OECD FORD obor

10201 - Computer sciences, information science, bioinformathics (hardware development to be 2.2, social aspect to be 5.8)

Projekt

—

Návaznosti

R - Projekt Ramcoveho programu EK

Rok uplatnění

2023

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název statě ve sborníku

26th European Conference on Artificial Intelligence ECAI 2023

ISBN

978-1-64368-436-9

ISSN

—

e-ISSN

—

Počet stran výsledku

8

Strana od-do

1922-1929

Název nakladatele

IOS Press BV

Místo vydání

Amsterdam, Netherlands

Místo konání akce

Kraków, Poland

Datum konání akce

30. 9. 2023

Typ akce podle státní příslušnosti

WRD - Celosvětová akce

Kód UT WoS článku

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