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Found 10 papers, 4 papers with code
PersonaSAGE: A Multi-Persona Graph Neural Network
Furthermore, PersonaSAGE learns the appropriate set of persona embeddings for each node in the graph, and every node can have a different number of assigned persona embeddings.
Bundle MCR: Towards Conversational Bundle Recommendation
MCR, which uses a conversational paradigm to elicit user interests by asking user preferences on tags (e. g., categories or attributes) and handling user feedback across multiple rounds, is an emerging recommendation setting to acquire user feedback and narrow down the output space, but has not been explored in the context of bundle recommendation.
CGC: Contrastive Graph Clustering for Community Detection and Tracking
Especially, deep graph clustering (DGC) methods have successfully extended deep clustering to graph-structured data by learning node representations and cluster assignments in a joint optimization framework.
VBridge: Connecting the Dots Between Features and Data to Explain Healthcare Models
Machine learning (ML) is increasingly applied to Electronic Health Records (EHRs) to solve clinical prediction tasks.
Insight-centric Visualization Recommendation
This global ranking makes it difficult and time-consuming for users to find the most interesting or relevant insights.
Personalized Visualization Recommendation
Visualization recommendation work has focused solely on scoring visualizations based on the underlying dataset and not the actual user and their past visualization feedback.
ML-based Visualization Recommendation: Learning to Recommend Visualizations from Data
Finally, we observed a strong preference by the human experts in our user study towards the visualizations recommended by our ML-based system as opposed to the rule-based system (5. 92 from a 7-point Likert scale compared to only 3. 45).
The Impact of Presentation Style on Human-In-The-Loop Detection of Algorithmic Bias
Semi-automated bias detection tools often present reports of automatically-detected biases using a recommendation list or visual cues.
Designing Tools for Semi-Automated Detection of Machine Learning Biases: An Interview Study
Machine learning models often make predictions that bias against certain subgroups of input data.
MetroViz: Visual Analysis of Public Transportation Data
Understanding the quality and usage of public transportation resources is important for schedule optimization and resource allocation.
Human-Computer Interaction
