A Study of Predictive Caching Using Local Storage and Machine Learning in Web Applications

@article{1717631,
      author = {Ayush Wange, Dr. Netraja Mulay},
      title = {A Study of Predictive Caching Using Local Storage and Machine Learning in Web Applications},
      journal = {Iconic Research And Engineering Journals},
      year = {2026},
      volume = {9},
      number = {11},
      pages = {1535-1538},
      issn = {2456-8880},
      url = {https://www.irejournals.com/formatedpaper/1717631.pdf},
      abstract = {This study explores improving web performance using Machine Learning–based predictive caching with localStorage. Traditional caching only stores previously visited content, which limits performance for first-time users. The proposed system predicts user behavior and preloads likely content in advance. The study compares no caching, traditional caching, and ML-based caching using metrics like LCP, FCP, and TTI. Results show significant improvements, with faster load times and higher cache efficiency using predictive caching. Overall, predictive caching provides a more efficient and responsive web experience than traditional methods.},
      keywords = {Localstorage, Predictive Caching, Machine Learning, Web Performance, LCP, FCP, TTI, Client-Side Caching, User Behavior Prediction.},
      month = {May},
      doi = {https://doi.org/10.64388/IREV9I11-1717631}
  }