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Predictive Prefetching Based on User Interaction for Web Applications

Authors
Joo, M.An, Y.Roh, H.Lee, W.
Issue Date
Mar-2021
Publisher
Institute of Electrical and Electronics Engineers Inc.
Keywords
quality of experience; user interaction; Web prefetching
Citation
IEEE Communications Letters, v.25, no.3, pp.821 - 824
Indexed
SCIE
SCOPUS
Journal Title
IEEE Communications Letters
Volume
25
Number
3
Start Page
821
End Page
824
URI
https://scholar.korea.ac.kr/handle/2021.sw.korea/49384
DOI
10.1109/LCOMM.2020.3038255
ISSN
1089-7798
Abstract
Web prefetching is a key technology to hide network latencies from users. Conventional prefetching methods, however, misconstrue the purpose of user's browsing behaviors and resulting experience due to their dependence on statistical characteristics or metadata of individual Web applications. In this letter, we propose a predictive prefetching scheme, WebPrefetcher, which utilizes interaction events to decipher user's genuine intention and context. Our intensive performance analysis results obtained with a real Web browser demonstrate that WebPrefetcher improves user-perceived quality of experience noticeably, outperforming competitive models. © 1997-2012 IEEE.
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