Abstract:
Disclosed are various embodiments for extracting an excerpt from a representative review of an item, such as an item available for purchase in an electronic commerce system. Attributes or categories used in reviews of an item may be identified and ranked according to consumer preference. Upon ranking the categories, an excerpt may be extracted from a review corresponding to a ranked one of the attributes or categories. The excerpt may be identified and extracted if a number of reviews for an item exceeds a threshold quantity as it may be impractical for a user to read every review written about the item.
Abstract:
Disclosed are various embodiments for extracting an excerpt from a representative review of an item, such as an item available for purchase in an electronic commerce system. Attributes or categories used in reviews of an item may be identified and ranked according to consumer preference. Upon ranking the categories, an excerpt may be extracted from a review corresponding to a ranked one of the attributes or categories. The excerpt may be identified and extracted if a number of reviews for an item exceeds a threshold quantity as it may be impractical for a user to read every review written about the item.
Abstract:
A resource delivery network and method for distributing content in the network is disclosed herein. The network comprises a plurality of servers arranged in tiers and partitioned. Each server includes a resource store with a set of resources for distribution to a successive tier. Updates to each successive tier are provided by a pull-forward client on servers in the tier. This forward propagation mechanism maximizes resource availability at edge servers in the network. Resources transmitted to the edge tier servers may be transformed, combined, and rendered without taxing lower tier servers. Transformation and pre-rendering of data can be performed by low priority CPU tasks at each layer of the system.
Abstract:
A resource delivery network and method for distributing content in the network is disclosed herein. The network comprises a plurality of servers arranged in tiers and partitioned. Each server includes a resource store with a set of resources for distribution to a successive tier. Updates to each successive tier are provided by a pull-forward client on servers in the tier. This forward propagation mechanism maximizes resource availability at edge servers in the network. Resources transmitted to the edge tier servers may be transformed, combined, and rendered without taxing lower tier servers. Transformation and pre-rendering of data can be performed by low priority CPU tasks at each layer of the system.