Advanced Web Optimization: Leveraging Neural Collaborative Filtering and Prefetching for Enhanced User Responsiveness

The continuous development of Internet technology has led to the widespread adoption of web applications, which are now indispensable in daily life. Users demand responsive websites and cannot afford long loading times. This research employs neural collaborative filtering to predict users’ next web pages and uses prefetching to improve loading speeds. An English learning website and the MovieLens 1M dataset were used for training, evaluation and testing. Results show that NeuMF, combining Generalized Matrix Factorisation (GMF) and Multi-layer Perceptron, significantly enhances web page response speeds through predictive prefetching.

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Publication Details

Published
2024-11-19
DOI
https://doi.org/10.1109/iceese62315.2024.10828552
Citations
1
Primary Topic
Recommender Systems and Techniques
Type
article
Field-Weighted Citation Impact
0.78
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article

Advanced Web Optimization: Leveraging Neural Collaborative Filtering and Prefetching for Enhanced User Responsiveness

Oras Baker, D.L. Liu, Wei Li
1 citations
Recommender Systems and Techniques
0.78
article

Advanced Web Optimization: Leveraging Neural Collaborative Filtering and Prefetching for Enhanced User Responsiveness

Oras Baker, D.L. Liu, Wei Li
article en
1 citations

Abstract

The continuous development of Internet technology has led to the widespread adoption of web applications, which are now indispensable in daily life. Users demand responsive websites and cannot afford long loading times. This research employs neural collaborative filtering to predict users’ next web pages and uses prefetching to improve loading speeds. An English learning website and the MovieLens 1M dataset were used for training, evaluation and testing. Results show that NeuMF, combining Generalized Matrix Factorisation (GMF) and Multi-layer Perceptron, significantly enhances web page response speeds through predictive prefetching.

Southern Institute of Technology (NZ), Ravensbourne University London (GB)
Openalex Percentile: Top 18%
Recommender Systems and Techniques
0.78
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