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Visualization for Recommendation Explainability: A Survey and New Perspectives
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Outgoing claims: the papers this work cites, builds on, or argues with.
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Explaining artificial intelligence with visual analytics in healthcare
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The Elaboration Likelihood Model of Persuasion
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Explaining Recommendations: Design and Evaluation
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Advances in Collaborative Filtering
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Semantics-Aware Content-Based Recommender Systems
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Personalising Explainable Recommendations: Literature and Conceptualisation
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Effects of Interactivity and Presentation on Review-Based Explanations for Recommendations
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An Interactive Node-Link Visualization of Convolutional Neural Networks
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Visual Analytics: Scope and Challenges
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A generalized taxonomy of explanations styles for traditional and social recommender systems
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Recommender systems: from algorithms to user experience
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Evaluating recommender systems from the user’s perspective: survey of the state of the art
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A systematic review and taxonomy of explanations in decision support and recommender systems
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The effects of controllability and explainability in a social recommender system
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Explanatory Interactive Machine Learning
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Recent research advances on interactive machine learning
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One Explanation Does Not Fit All
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Information Visualization: Perception for Design
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Explanation in artificial intelligence: Insights from the social sciences
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A human cognition framework for information visualization
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Interactive recommender systems: A survey of the state of the art and future research challenges and opportunities
inferredcites →https://doi.org/10.1016/j.eswa.2017.01.045openalex-snapshot
Make it personal: A social explanation system applied to group recommendations
inferredcites →https://doi.org/10.1016/j.ijhcs.2013.12.007openalex-snapshot
How should I explain? A comparison of different explanation types for recommender systems
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Moodplay: Interactive music recommendation based on Artists’ mood similarity
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Interactive recommending with Tag-Enhanced Matrix Factorization (TagMF)
inferredcites →https://doi.org/10.1016/j.inffus.2019.12.012openalex-snapshot
Explainable Artificial Intelligence (XAI): Concepts, taxonomies, opportunities and challenges toward responsible AI
inferredcites →https://doi.org/10.1016/j.visinf.2017.01.006openalex-snapshot
Towards better analysis of machine learning models: A visual analytics perspective
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Representativeness Revisited: Attribute Substitution in Intuitive Judgment
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Conversational processes and causal explanation.
inferredcites →https://doi.org/10.1038/s42256-020-0212-3openalex-snapshot
Making deep neural networks right for the right scientific reasons by interacting with their explanations
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Interactive Explanation with Varying Level of Details in an Explainable Scientific Literature Recommender System
inferredcites →https://doi.org/10.1109/access.2019.2923736openalex-snapshot
Visual Analytics: A Comprehensive Overview
inferredcites →https://doi.org/10.1109/access.2019.2934633openalex-snapshot
Mining Semantic Knowledge Graphs to Add Explainability to Black Box Recommender Systems
inferredcites →https://doi.org/10.1109/achi.2008.36openalex-snapshot
Towards Leveraging Inference Web to Support Intuitive Explanations in Recommender Systems for Automated Career Counseling
inferredcites →https://doi.org/10.1109/icdew.2007.4401070openalex-snapshot
A Survey of Explanations in Recommender Systems
inferredcites →https://doi.org/10.1109/mc.2009.263openalex-snapshot
Matrix Factorization Techniques for Recommender Systems
inferredcites →https://doi.org/10.1109/mcg.2006.70openalex-snapshot
Toward measuring visualization insight
inferredcites →https://doi.org/10.1109/mcg.2018.042731661openalex-snapshot
Visual Analytics for Explainable Deep Learning
inferredcites →https://doi.org/10.1109/tkde.2019.2906190openalex-snapshot
Explainable Outfit Recommendation with Joint Outfit Matching and Comment Generation
inferredcites →https://doi.org/10.1109/tvcg.2014.2346419openalex-snapshot
The Persuasive Power of Data Visualization
inferredcites →https://doi.org/10.1109/tvcg.2016.2598838openalex-snapshot
Visualizing the Hidden Activity of Artificial Neural Networks
inferredcites →https://doi.org/10.1109/tvcg.2017.2744158openalex-snapshot
LSTMVis: A Tool for Visual Analysis of Hidden State Dynamics in Recurrent Neural Networks
inferredcites →https://doi.org/10.1109/tvcg.2017.2744683openalex-snapshot
Do Convolutional Neural Networks Learn Class Hierarchy?
inferredcites →https://doi.org/10.1109/tvcg.2017.2744878openalex-snapshot
Visualizing Dataflow Graphs of Deep Learning Models in TensorFlow
inferredcites →https://doi.org/10.1109/tvcg.2018.2843369openalex-snapshot
Visual Analytics in Deep Learning: An Interrogative Survey for the Next Frontiers
inferredcites →https://doi.org/10.1109/tvcg.2018.2864500openalex-snapshot
GAN Lab: Understanding Complex Deep Generative Models using Interactive Visual Experimentation
inferredcites →https://doi.org/10.1109/tvcg.2018.2865027openalex-snapshot
RetainVis: Visual Analytics with Interpretable and Interactive Recurrent Neural Networks on Electronic Medical Records
inferredcites →https://doi.org/10.1109/tvcg.2019.2934629openalex-snapshot
explAIner: A Visual Analytics Framework for Interactive and Explainable Machine Learning
inferredcites →https://doi.org/10.1109/tvcg.2020.3030418openalex-snapshot
CNN Explainer: Learning Convolutional Neural Networks with Interactive Visualization
inferredcites →https://doi.org/10.1109/vis4good57762.2022.00005openalex-snapshot
Can Data Visualizations Change Minds? Identifying Mechanisms of Elaborative Thinking and Persuasion
inferredcites →https://doi.org/10.1111/cgf.13092openalex-snapshot
The State of the Art in Integrating Machine Learning into Visual Analytics
inferredcites →https://doi.org/10.1111/cgf.13210openalex-snapshot
The State‐of‐the‐Art in Predictive Visual Analytics
inferredcites →https://doi.org/10.1111/cgf.14034openalex-snapshot
The State of the Art in Enhancing Trust in Machine Learning Models with the Use of Visualizations
inferredcites →https://doi.org/10.1111/j.1467-8659.2009.01679.xopenalex-snapshot
SmallWorlds: Visualizing Social Recommendations
inferredcites →https://doi.org/10.1145/1518701.1519023openalex-snapshot
Why and why not explanations improve the intelligibility of context-aware intelligent systems
inferredcites →https://doi.org/10.1145/1620545.1620576openalex-snapshot
Assessing demand for intelligibility in context-aware applications
inferredcites →https://doi.org/10.1145/1743546.1743567openalex-snapshot
A tour through the visualization zoo
inferredcites →https://doi.org/10.1145/2043932.2043962openalex-snapshot
A user-centric evaluation framework for recommender systems
inferredcites →https://doi.org/10.1145/2245276.2232109openalex-snapshot
The relation between user intervention and user satisfaction for information recommendation
inferredcites →https://doi.org/10.1145/2449396.2449405openalex-snapshot
An approach to controlling user models and personalization effects in recommender systems
inferredcites →https://doi.org/10.1145/2449396.2449442openalex-snapshot
Visualizing recommendations to support exploration, transparency and controllability
inferredcites →https://doi.org/10.1145/2507157.2507163openalex-snapshot
Hidden factors and hidden topics
inferredcites →https://doi.org/10.1145/2600428.2609579openalex-snapshot
Explicit factor models for explainable recommendation based on phrase-level sentiment analysis
inferredcites →https://doi.org/10.1145/2678025.2701371openalex-snapshot
Improving Controllability and Predictability of Interactive Recommendation Interfaces for Exploratory Search
inferredcites →https://doi.org/10.1145/2678025.2701399openalex-snapshot
Principles of Explanatory Debugging to Personalize Interactive Machine Learning
inferredcites →https://doi.org/10.1145/3001837openalex-snapshot
Interacting with Recommenders—Overview and Research Directions
inferredcites →https://doi.org/10.1145/3009976openalex-snapshot
Supporting Exploratory Search with a Visual User-Driven Approach
inferredcites →https://doi.org/10.1145/3079628.3079701openalex-snapshot
Providing Control and Transparency in a Social Recommender System for Academic Conferences
inferredcites →https://doi.org/10.1145/3172944.3172961openalex-snapshot
Bringing Transparency Design into Practice
inferredcites →https://doi.org/10.1145/3173574.3174156openalex-snapshot
Trends and Trajectories for Explainable, Accountable and Intelligible Systems
inferredcites →https://doi.org/10.1145/3180308.3180368openalex-snapshot
Explaining Social Recommendations to Casual Users
inferredcites →https://doi.org/10.1145/3185517openalex-snapshot
A Review of User Interface Design for Interactive Machine Learning
inferredcites →https://doi.org/10.1145/3209219.3209225openalex-snapshot
Effects of Individual Traits on Diversity-Aware Music Recommender User Interfaces
inferredcites →https://doi.org/10.1145/3240323.3240358openalex-snapshot
Effects of personal characteristics on music recommender systems with different levels of controllability
inferredcites →https://doi.org/10.1145/3290605.3300789openalex-snapshot
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inferredcites →https://doi.org/10.1145/3298689.3347014openalex-snapshot
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inferredcites →https://doi.org/10.1145/3301275.3302306openalex-snapshot
Personalized explanations for hybrid recommender systems
inferredcites →https://doi.org/10.1145/3301275.3302318openalex-snapshot
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inferredcites →https://doi.org/10.1145/3306618.3314293openalex-snapshot
Explanatory Interactive Machine Learning
inferredcites →https://doi.org/10.1145/3313831.3376590openalex-snapshot
Questioning the AI: Informing Design Practices for Explainable AI User Experiences
inferredcites →https://doi.org/10.1145/3331184.3331211openalex-snapshot
Transparent, Scrutable and Explainable User Models for Personalized Recommendation
inferredcites →https://doi.org/10.1145/3331184.3331254openalex-snapshot
Personalized Fashion Recommendation with Visual Explanations based on Multimodal Attention Network
inferredcites →https://doi.org/10.1145/3340631.3394841openalex-snapshot
Exploring Mental Models for Transparent and Controllable Recommender Systems: A Qualitative Study
inferredcites →https://doi.org/10.1145/3345002.3349293openalex-snapshot
Explanations and User Control in Recommender Systems
inferredcites →https://doi.org/10.1145/3377325.3377480openalex-snapshot
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inferredcites →https://doi.org/10.1145/3387166openalex-snapshot
A Multidisciplinary Survey and Framework for Design and Evaluation of Explainable AI Systems
inferredcites →https://doi.org/10.1145/3397481.3450662openalex-snapshot
Visual, textual or hybrid: the effect of user expertise on different explanations
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Bridging the Gap Between Ethics and Practice
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On-demand Personalized Explanation for Transparent Recommendation
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A Survey on Conversational Recommender Systems
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Exploring the Effects of Interactive Dialogue in Improving User Control for Explainable Online Symptom Checkers
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Putting Environmental Infographics Center Stage
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Effects of infographics on news elaboration, acquisition, and evaluation: Prior knowledge and issue involvement as moderators
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Dual-Process Theories of Higher Cognition
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Decision making with visualizations: a cognitive framework across disciplines
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Explainable Recommendation: A Survey and New Perspectives
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The Elaboration Likelihood Model
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Interactive Infographics' Effect on Elaboration in Agricultural Communication
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Direct-Manipulation Visualization of Deep Networks
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UniWalk: Explainable and Accurate Recommendation for Rating and Network Data
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Incoming claims: where this work appears in other papers’ reference lists and arguments.
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AI Architectures for Intelligent Shopping Agents
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