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Found 5 papers, 2 papers with code
MobileRec: A Large-Scale Dataset for Mobile Apps Recommendation
To facilitate research for app recommendation systems, we introduce a large-scale dataset, called MobileRec.
Proactive Prioritization of App Issues via Contrastive Learning
Phase one adapts the pre-trained T5 model to the user reviews data in a self-supervised fashion.
Pasture Intake Protects Against Commercial Diet-induced Lipopolysaccharide Production Facilitated by Gut Microbiota through Activating Intestinal Alkaline Phosphatase Enzyme in Meat Geese
In the gut microbiota analysis, meat geese supplemented with pasture demonstrated a significant reduction in microbial richness and diversity compared to IHF meat geese demonstrating antimicrobial, antioxidation, and anti-inflammatory ability of AGF system.
App-Aware Response Synthesis for User Reviews
Solving the challenge by simply building a model per app (i. e., training with review-response pairs of a single app) may be insufficient because individual apps have limited review-response pairs, and such pairs typically lack the relevant information needed to respond to a new review.
Measuring LDA Topic Stability from Clusters of Replicated Runs
For the clusters, we try multiple stability metrics, out of which we recommend Rank-Biased Overlap, showing the stability of the topics inside the clusters.
