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Reinforcement recommendation reasoning through knowledge graphs for explanation path quality

  • Published:2023-01 Issue: Volume:260 Page:110098
  • ISSN:0950-7051
  • Container-title:Knowledge-Based Systems
  • language:en
  • Short-container-title:Knowledge-Based Systems

Author:

Balloccu GiacomoORCID,Boratto LudovicoORCID,Fenu Gianni,Marras MirkoORCID

Publisher

Elsevier BV

Subject

Artificial Intelligence,Information Systems and Management,Management Information Systems,Software

Reference43 articles.

1. European union regulations on algorithmic decision-making and a “right to explanation”;Goodman;AI Mag.,2017

2. A survey of explanations in recommender systems;Tintarev,2007

3. Reinforcement knowledge graph reasoning for explainable recommendation;Xian,2019

4. Interpretable and efficient heterogeneous graph convolutional network;Yang;IEEE Trans. Knowl. Data Eng.,2021

5. Metonr: A meta explanation triplet oriented news recommendation model;Zhang;Know.-Based Syst.,2022

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2. Learner-centered Ontology for Explainable Educational Recommendation;Adjunct Proceedings of the 32nd ACM Conference on User Modeling, Adaptation and Personalization;2024-06-27

3. TeReKG: A temporal collaborative knowledge graph framework for software team recommendation;Knowledge-Based Systems;2024-04

4. First International Workshop on Graph-Based Approaches in Information Retrieval (IRonGraphs 2024);Lecture Notes in Computer Science;2024

5. Explainable Recommender Systems with Knowledge Graphs and Language Models;Lecture Notes in Computer Science;2024
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