Facebook, Inc.

Meta Platforms, Inc.

Flatiron Health, Inc.

Gil Shklarski

Christopher Alexander Stein

Nickolay Vladimirov Tchervenski

Bhalchandra Suresh Agashe

Dennis Lee

Benjamin Edward Birnbaum

Nathan Coleman Nussbaum

Joseph Delgado

Paul Stephen Richardson

Melisa Tucker

Dominique Connolly

Cynthia Revol

Joseph Mou

Daniel Eisenberg

Geoffrey Calkins

Maayan Roth

Lauren Ellsworth

Nathaniel Turner

Zachary Weinberg

Ross Feinstein

Paul You

Jeremy Feinstein

Caitlin Keenan

Joseph DiLallo

Jeremy Kohansimeh

Elijah Meerson

Amy Abernethy

James Dura

Catherine Miller

Some embodiments include tracking events and classifying assets within a computer system. A time series of occurrences of an event type associated with at least one asset is generated. A first signal value and a second signal value is determined based on the time series. The at least one asset can be classified based on comparison of the first signal value and the second signal value. The time series can be based on at least one time window including time intervals. Counters to determine a number of occurrences of an event type can be associated with the time intervals. Each of the counters can be incremented upon occurrence of the event type associated with the at least one asset during an associated time interval.

Systems and methods for event tracking using time-windowed counters

Methods, systems, and apparatus, including computer programs encoded on computer storage media, to present a video. One of the methods includes obtaining one or more unstructured documents. The method includes obtaining, by a computer system, a data model, the data model identifying a type of fact that can be determined from the one or more unstructured documents. The method includes determining, by the computer system, a channel to extract facts from the document based on the type of fact. The method includes distributing, by the computer system, the one or more unstructured documents to the channel. The method includes extracting, by the channel, facts from the one or more unstructured documents. The method also includes storing the facts in a data model.

Extracting facts from unstructured data

To allow for tracking events and classifying assets within a social networking system. A time series of occurrences of an event type associated with at least one asset is generated. A first signal value and a second signal value is determined based on the time series. The at least one asset is classified based on comparison of the first signal value and the second signal value. In an embodiment, the time series is based on at least one time window including time intervals. In an embodiment, counters to determine a number of occurrences of an event type are associated with the time intervals. In an embodiment, each of the counters are incremented upon occurrence of the event type associated with the at least one asset during an associated time interval.

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New York, NY, United States of America

Gil Shklarski