Amazon Technologies, Inc.

Limelight Networks, Inc.

Ahmed A Badran

James E Scharf, Jr

Peter Grant Gavares

Govindaswamy Bacthavachalu

Soam Acharya

Spencer Proffit

Gavindaswamy Bacthavachalu

Data can be processed in parallel across a cluster of nodes using a parallel processing framework. Using Web services calls between components allows the number of nodes to be scaled as necessary, and allows developers to build applications on the framework using a Web services interface. A job scheduler works together with a queuing service to distribute jobs to nodes as the nodes have capacity, such that jobs can be performed in parallel as quickly as the nodes are able to process the jobs. Data can be loaded efficiently across the cluster, and levels of nodes can be determined dynamically to process queries and other requests on the system.

Dynamic tree determination for data processing

Parallel processing framework

Methods and systems generate content-categorization hierarchies and assign each content object to a set of nodes in the hierarchies. Each hierarchy includes a series of levels, each level including nodes which represent a categorization. A node in a top level is connected with multiple nodes in a lower level via a direct path. Each content object is assigned to a set of nodes, such that assignment to a lower-level node also results in assignment to each higher-level node in the lower-level node's direct path to a top of the hierarchy. Metadata of the content object is then modified to include a set of tags, each tag being a term from an assigned node. Tags are used to categorize the content object, summarize of the content object, identify recommended content objects, identify content objects responsive to a search query, and/or identify other content objects to supplement the content object.

Content tagging using multi-node hierarchical content assignments

Growing community of inventors

Issaquah, WA, United States of America

Ahmed A Badran