Tubular Labs, Inc.

Aol Advertising Inc.

Scott Strickland

Ioannis Mantzouratos

Dmytro Popovych

Niklas Karlsson

Robert Luenberger

Jianlong Zhang

Li Si Yang

Yih-Shin Huang

Hans W Uhlig

Seyed Mohammad Ziaemohseni

Efficient evaluation of sets of resources is disclosed, including: determining a first plurality of representations from identifying information associated with a first set of resources; updating a first data structure corresponding to the first set of resources using portions of respective ones of the first plurality of representations; determining a second plurality of representations from identifying information associated with a second set of resources; updating a second data structure corresponding to the second set of resources using portions of respective ones of the second plurality of representations; and using the first data structure and the second data structure to compute a derived value associated with the first set of resources and the second set of resources.

Efficient evaluation of sets of resources

Efficient aggregation of time series data is disclosed, including: obtaining a first entry value corresponding to an item, wherein the first entry value comprises a first recorded data point that is associated with a first time interval; generating a compressed block based at least in part on compressing the first entry value with at least a second entry value; storing the compressed block in a document corresponding to the item; determining that the item matches an aggregation search query; decompressing the compressed block from the document corresponding to the item to obtain the first entry value and the second entry value; and generating an aggregation result in response to the aggregation search query based on at least a portion of the first entry value and the second entry value.

Efficient aggregation of time series data

System and methods are provided for analyzing and displaying digital content and advertisements over electronic networks. In accordance with one implementation, a method is provided that calculates, using at least one processor, an engagement metric (including, for example, click probability) for a specific combination of time, promotion slot, and user segment, for an individual promotion of a set of promotions, and calculates a value of a landing page associated with the promotion. The method then can multiply the engagement metric and the value to determine the valuation of the promotion. The method can operate recursively by using previous calculations in later runs of the same method.

Systems and methods for displaying digital content and advertisements over electronic networks

Growing community of inventors

Redwood City, CA, United States of America

Scott Strickland