MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction
MISApp: Multi-Hop Intent-Aware Session Graph Learning for Next App Prediction explores A profile-free framework for next app prediction using multi-hop session graph learning to capture evolving user intent, outperforming baselines in real-world scenarios.. Commercial viability score: 7/10 in Mobile AI.
BUILDER'S SANDBOX
Build This Paper
Use an AI coding agent to implement this research.
OpenAI CodexAI Agent
Lightweight coding agent in your terminal.
Claude CodeAI Agent
Agentic coding tool for terminal workflows.
AntiGravity IDEScaffolding
AI agent mindset installer and workflow scaffolder.
CursorIDE
AI-first code editor built on VS Code.
VS CodeIDE
Free, open-source editor by Microsoft.
Recommended Stack
Startup Essentials
Estimated $9K - $13K over 6-10 weeks.
See exactly what it costs to build this -- with 3 comparable funded startups.
7-day free trial. Cancel anytime.
Discover the researchers behind this paper and find similar experts.
7-day free trial. Cancel anytime.
Related Papers
- Builds On ThisMultimodal Graph Representation Learning with Dynamic Information PathwaysViability: 4.0
- Prior WorkLearning Next Action Predictors from Human-Computer InteractionViability: 7.0
- Prior WorkModeling Stage-wise Evolution of User Interests for News RecommendationViability: 7.0
- Prior WorkStochastic Event Prediction via Temporal Motif TransitionsViability: 7.0
- Prior WorkA Multi-Scale Graph Learning Framework with Temporal Consistency Constraints for Financial Fraud Detection in Transaction Networks under Non-Stationary Conditions