research-article

Explaining recommendations by means of aspect-based transparent memories

Authors:

Jürgen ZieglerAuthors Info & Claims

IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces

Pages 166 - 176

https://doi.org/10.1145/3377325.3377520

Published: 17 March 2020 Publication History

Abstract

Recommender Systems have seen substantial progress in terms of algorithmic sophistication recently. Yet, the systems mostly act as black boxes and are limited in their capacity to explain why an item is recommended. In many cases recommendations methods are employed in scenarios where users not only rate items, but also convey their opinion on various relevant aspects, for instance by the means of textual reviews. Such user-generated content can serve as a useful source for deriving explanatory information to increase system intelligibility and, thereby, the user's understanding.

We propose a recommendation and explanation method that exploits the comprehensiveness of textual data to make the underlying criteria and mechanisms that lead to a recommendation more transparent. Concretely, the method incorporates neural memories that store aspect-related opinions extracted from raw review data. We apply attention mechanisms to transparently write and read information from memory slots.

Besides customary offline experiments, we conducted an extensive user study. The results indicate that our approach achieves a higher overall quality of explanations compared to a state-of-the-art baseline. Utilizing Structural Equation Modeling, we additionally reveal three linked key factors that constitute explanation quality: Content adequacy, presentation adequacy, and linguistic adequacy.

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Cited By

Al-Ansari NAl-Thani DAl-Mansoori R(2024)User‐Centered Evaluation of Explainable Artificial Intelligence (XAI): A Systematic Literature ReviewHuman Behavior and Emerging Technologies10.1155/2024/46288552024:1Online publication date: 15-Jul-2024
https://doi.org/10.1155/2024/4628855
Kotkov DMedlar ALiu YGlowacka DHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)On the Negative Perception of Cross-domain Recommendations and ExplanationsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657735(2102-2113)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657735
Rong YLeemann TNguyen TFiedler LQian PUnhelkar VSeidel TKasneci GKasneci E(2024)Towards Human-Centered Explainable AI: A Survey of User Studies for Model ExplanationsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.333184646:4(2104-2122)Online publication date: Apr-2024
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Explaining recommendations by means of aspect-based transparent memories

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cover image ACM Conferences

IUI '20: Proceedings of the 25th International Conference on Intelligent User Interfaces

March 2020

607 pages

ISBN:9781450371186

DOI:10.1145/3377325

General Chairs:
Fabio Paternò,
Nuria Oliver,
Program Chairs:
Cristina Conati,
Lucio Davide Spano,
Nava Tintarev

Copyright © 2020 ACM.

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Published: 17 March 2020

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IUI '20: 25th International Conference on Intelligent User Interfaces

March 17 - 20, 2020

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Overall Acceptance Rate 746 of 2,811 submissions, 27%

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Cited By

Al-Ansari NAl-Thani DAl-Mansoori R(2024)User‐Centered Evaluation of Explainable Artificial Intelligence (XAI): A Systematic Literature ReviewHuman Behavior and Emerging Technologies10.1155/2024/46288552024:1Online publication date: 15-Jul-2024
https://doi.org/10.1155/2024/4628855
Kotkov DMedlar ALiu YGlowacka DHui Yang GWang HHan SHauff CZuccon GZhang Y(2024)On the Negative Perception of Cross-domain Recommendations and ExplanationsProceedings of the 47th International ACM SIGIR Conference on Research and Development in Information Retrieval10.1145/3626772.3657735(2102-2113)Online publication date: 10-Jul-2024
https://dl.acm.org/doi/10.1145/3626772.3657735
Rong YLeemann TNguyen TFiedler LQian PUnhelkar VSeidel TKasneci GKasneci E(2024)Towards Human-Centered Explainable AI: A Survey of User Studies for Model ExplanationsIEEE Transactions on Pattern Analysis and Machine Intelligence10.1109/TPAMI.2023.333184646:4(2104-2122)Online publication date: Apr-2024
https://doi.org/10.1109/TPAMI.2023.3331846
Brachman MPan QDo HDugan CChaudhary AJohnson JRai PChakraborti TGschwind TLaredo JMiksovic CScotton PTalamadupula KThomas G(2023)Follow the Successful Herd: Towards Explanations for Improved Use and Mental Models of Natural Language SystemsProceedings of the 28th International Conference on Intelligent User Interfaces10.1145/3581641.3584088(220-239)Online publication date: 27-Mar-2023
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Hernandez-Bocanegra DZiegler J(2023)Explaining Recommendations through Conversations: Dialog Model and the Effects of Interface Type and Degree of InteractivityACM Transactions on Interactive Intelligent Systems10.1145/357954113:2(1-47)Online publication date: 12-Apr-2023
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Bhojwani AJolly VGoel SM A(2023)Aspect Based Neural Recommender Using Adaptive Prediction2023 IEEE International Students' Conference on Electrical, Electronics and Computer Science (SCEECS)10.1109/SCEECS57921.2023.10063025(1-7)Online publication date: 18-Feb-2023
https://doi.org/10.1109/SCEECS57921.2023.10063025
Kleemann TZiegler J(2023)Blending Conversational Product Advisors and Faceted Filtering in a Graph-Based ApproachHuman-Computer Interaction – INTERACT 202310.1007/978-3-031-42286-7_8(137-159)Online publication date: 28-Aug-2023
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Buschek DEiband MHussmann H(2022)How to Support Users in Understanding Intelligent Systems? An Analysis and Conceptual Framework of User Questions Considering User Mindsets, Involvement, and Knowledge OutcomesACM Transactions on Interactive Intelligent Systems10.1145/351926412:4(1-27)Online publication date: 5-Nov-2022
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Ben Zaken DSegal ACavalier DShani GGal KBellogin ABoratto LSantos OArdissono LKnijnenburg B(2022)Generating Recommendations with Post-Hoc Explanations for Citizen ScienceProceedings of the 30th ACM Conference on User Modeling, Adaptation and Personalization10.1145/3503252.3531290(69-78)Online publication date: 4-Jul-2022
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Ooge JKato SVerbert K(2022)Explaining Recommendations in E-Learning: Effects on Adolescents' TrustProceedings of the 27th International Conference on Intelligent User Interfaces10.1145/3490099.3511140(93-105)Online publication date: 22-Mar-2022
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