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  • i-com Band 19 (2020) Heft 3
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Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics

Autor(en):
Hernandez-Bocanegra, Diana C. [DBLP] ;
Ziegler, Jürgen [DBLP]
Zusammenfassung
Providing explanations based on user reviews in recommender systems (RS) may increase users’ perception of transparency or effectiveness. However, little is known about how these explanations should be presented to users, or which types of user interface components should be included in explanations, in order to increase both their comprehensibility and acceptance. To investigate such matters, we conducted two experiments and evaluated the differences in users’ perception when providing information about their own profiles, in addition to a summarized view on the opinions of other customers about the recommended hotel. Additionally, we also aimed to test the effect of different display styles (bar chart and table) on the perception of review-based explanations for recommended hotels, as well as how useful users find different explanatory interface components. Our results suggest that the perception of an RS and its explanations given profile transparency and different presentation styles, may vary depending on individual differences on user characteristics, such as decision-making styles, social awareness, or visualization familiarity.
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  • BibTeX
Hernandez-Bocanegra, D. C. & Ziegler, J., (2021). Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics.   i-com: Vol. 19, No. 3. Berlin: De Gruyter. (S. 181-200). DOI: 10.1515/icom-2020-0021
@article{mci/Hernandez-Bocanegra2021,
author = {Hernandez-Bocanegra, Diana C. AND Ziegler, Jürgen},
title = {Explaining Review-Based Recommendations: Effects of Profile Transparency, Presentation Style and User Characteristics},
journal = {i-com},
volume = {19},
number = {3},
year = {2021},
,
pages = { 181-200 } ,
doi = { 10.1515/icom-2020-0021 }
}

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Mehr Information

DOI: 10.1515/icom-2020-0021
ISSN: 2196-6826
Datum: 2021
Sprache: en (en)
Typ: Text/Journal Article

Keywords

  • Recommender systems
  • user study
  • explanations
Sammlungen
  • i-com Band 19 (2020) Heft 3 [8]

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Diese Digital Library basiert auf DSpace.

 

 


Über uns | FAQ | Hilfe | Impressum | Datenschutz

Gesellschaft für Informatik e.V. (GI), Kontakt: Geschäftsstelle der GI
Diese Digital Library basiert auf DSpace.