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Data saving using contextual signals Disclosure Number: IPCOM000255940D
Publication Date: 2018-Oct-24
Document File: 8 page(s) / 545K

Publishing Venue

The Prior Art Database


Mobile device applications and operating systems offer a data-saving option such that
online content that is believed to be unchanged since last load is not reloaded. However, this
sometimes leads to a situation where online content that has actually changed is not reloaded or
that stale content is reloaded. The misdetection of fresh content as stale or vice-versa occurs due
to the heuristics that are used by the data-saving algorithms of the application/ OS, due to
misconfigured servers, etc.
This disclosure presents machine-learning techniques that determine if a web page or a
portion thereof is to be reloaded. The techniques use various contextual signals, as permitted by
the user, to make the reload decision, e.g., the content to be reloaded; surrounding content; their
metadata and positions on a web-page; user interaction and behavior with the website; previously
loaded content; etc. The techniques enable data-saving techniques that are robust and tailored to
both user and website.
● mobile data
● page reload
● page refresh
● stale content
● smart refresh
● data saving
● web browser