Hernandez-Bocanegra, Diana Carolina; Ziegler, Jürgen:
Assessing the Helpfulness of Review Content for Explaining Recommendations
In: EARS 2019 : The 2nd International Workshop on ExplainAble Recommendation and Search - 2nd International Workshop on ExplainAble Recommendation and Search, EARS’19, 25 July 2019, Paris, France - New York: ACM, 2019
2019Buchaufsatz/Kapitel in TagungsbandOA Grün
InformatikFakultät für Ingenieurwissenschaften » Informatik und Angewandte Kognitionswissenschaft » Informatik » Interaktive Systeme / Interaktionsdesign
Titel in Englisch:
Assessing the Helpfulness of Review Content for Explaining Recommendations
Autor*in:
Hernandez-Bocanegra, Diana CarolinaUDE
GND
1256307963
LSF ID
60092
ORCID
0000-0002-1773-2633ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
;
Ziegler, JürgenUDE
GND
1015876811
LSF ID
3881
ORCID
0000-0001-9603-5272ORCID iD
Sonstiges
der Hochschule zugeordnete*r Autor*in
Open Access?:
OA Grün
arXiv.org ID
Sprache des Textes:
Englisch
Schlagwort, Thema:
Recommender systems, explanations

Abstract in Englisch:

Despite the maturity already achieved by recommender systems algorithms, little is known about how to obtain and provide users with a proper rationale for a recommendation. Transparency and effectiveness of recommender systems may be increased when explanations are provided. In particular, identifying of helpful argumentative content from reviews can be leveraged to generate textual explanations. In this paper, we investigate the reasons why a review might be considered helpful, and show that the perception of credibility and convincingness mediates the relationship between helpfulness and the perception of objectivity and relevant aspects addressed. Our findings led us to suggest an argumentbased approach to automatically extracting helpful content from hotel reviews, a domain that differs from those that best fit classical argumentation theories.