Predictive caching and fetch priority

摘要

Predicting what content items a user finds important and sending those items to a cache on the user's device at times when doing so will not drain resources and will not result in expensive data rates. Applying a ranking function that examines recency and other content metadata associated with the user's content items stored in a synchronized content management system. Determining how much of a ranked list of content items to cache and deciding when is a good time to send content items to the local cache.

主权项

1. A computer-implemented method comprising:
receiving, from a mobile device, an amount of free memory available for caching one or more content items from a collection of content items stored in a synchronized content management system, wherein each of the content items in the collection of content items has associated metadata, wherein the metadata associated with a content item comprises:
a File Score calculated based on one or more recency-related events selected from among:a most recent occurrence of a user of the mobile device opening the content item using an application offered by the synchronized content management system,a most recent occurrence of the user of the mobile device opening the content item using a third party application,a most recent occurrence of the user of the mobile device sharing the content item via the mobile device,a most recent occurrence of another user of the synchronized content management system sharing the content item with the user of the mobile device,a most recent occurrence of the user of the mobile device sharing the content item via another electronic device,a most recent occurrence of the user of the mobile device editing the content item, ora most recent occurrence of the user of the mobile device accessing the content item via another electronic device; generating, via at least one processor, a scaling factor for each of the content items in the collection based on the associated metadata; and selecting a subset of content items from the collection based on the generated scaling factors and the amount of free space.