MAPLE: Mobile App Prediction Leveraging Large Language Model Embeddings

In recent years, predicting mobile app usage has become increasingly important for areas like app recommendation, user behaviour analysis, and mobile resource management. Existing models, however, struggle with the heterogeneous nature of contextual data and the user cold start problem. This study introduces a novel prediction model, Mobile App Prediction Leveraging Large Language Model Embeddings (MAPLE), which employs Large Language Models (LLMs) and installed app similarity to overcome these challenges. MAPLE utilises the power of LLMs to process contextual data …

analysis app become cold start cs.ai cs.cl data embeddings language language model large language large language model management mobile mobile app nature novel prediction recommendation struggle study usage