Amazon Technologies, Inc.

Shen Li

Rui Chen

Murali Brahmadesam

Sameer R Rajyaguru

Serguei B Stepaniants

Michael Luis Collado

Andrew Christopher Schleit

Robert Andrew Kreek

Kevin Donald Kelly

Andrei N Krotkov

Ajay Kant Singh

Ray Chen

Donald Kane

Richard Bargreen

Vignesh Kannappan

Pramod Muralidharan

Hancao Li

Technologies are disclosed for determining network-accessible content changes based on computed models and providing a long term forecast of user interaction at a network accessible site based upon a short term experiment at the site. A forecast model for a period of time is generated based upon historical data of user interactions at the site. An experiment is run for a short term at the site based upon a potential change at the site. Based upon data obtained during the experiment, scores are generated for a control group (no change) and a treatment group (potential change) and compared. If there are statistically significant differences between the control group and the treatment group scores, the long term forecast may be used to forecast what the long term impact of the experiment would be based upon the short term experiment.

Computationally and network bandwidth-efficient technique to determine network-accessible content changes based on computed models

Described are techniques for maintaining the accuracy of a precomputed output by determining sets of instructions for accessing and extracting values from individual data sources used to determine the output. Responsive to the determination of a modification to data in the data source, the data sources may be accessed to determine values that may be used to modify the precomputed output. The sets of instructions for accessing the data sources may be determined based on the relationships between different data sources and between one or more data sources and the output.

System for maintaining precomputed values determined from data sources

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Issaquah, WA, United States of America

Shen Li