Groupon, Inc.

Bytedance Inc.

Shawn Ryan Jeffery

Nick Pendar

David Alan Johnston

Matthew DeLand

Mark Thomas Daly

Andrew James

Richard Clark Barber

Gaston L'Huillier

Hernan Enrique Arroyo Garcia

Jonathan Esterhazy

Francisco Jose Larrain

Dor Levi

Amit Koren

Daniel Langdon

Bhupesh Bansal

Feras Karablieh

Srinivasa Raghavan Vedanarayanan

Juzheng Li

Shafiq Shariff

Rajesh Girish Parekh

Derek Nordquist

Matt DeLand

Bob Beaty

Rajat Bhattacharjee

Brian Mullins

Kris Urie

Michael Busch

Vasileios Polychronopoulos

Liwen Sun

In general, embodiments of the present invention provide systems, methods and computer readable media for identifying a new business based on programmatically analyzing content received from online sources and, as a result, discovering one or more references to the business. In embodiments, the system stores historical data representing previously identified new businesses and then uses attributes of those businesses in search queries to receive related content. Additionally or alternatively, the system stores data representing online sources that historically provided content containing references to new businesses and then continues to access those sources for additional content. In embodiments, the system performs content analysis on structured and/or unstructured content. In some embodiments, analysis of content received from a particular online source includes a source-specific algorithm that takes a source-specific representation of the content as input and produces a result indicating the likelihood that the content includes a new business reference.

Discovery of new business openings using web content analysis

Embodiments provide a computer-executable method, computer system and non-transitory computer-readable medium for programmatically analyzing a consumer review. The method includes programmatically accessing, via a network device, one or more consumer reviews for a commercial entity or a commercial object. The method also includes executing a consumer review processing engine to programmatically identify an attribute descriptor in the one or more consumer reviews, and executing the consumer review processing engine to programmatically generate a sentiment score associated with the one or more consumer reviews. The method further includes storing, on a non-transitory computer-readable storage device, the attribute descriptor and the sentiment score in association with the commercial entity or the commercial object.

Method and system for programmatic analysis of consumer reviews

In general, embodiments of the present invention provide systems, methods and computer readable media for automated dynamic data quality assessment. One aspect of the subject matter described in this specification includes the actions of receiving a data quality job including a new data sample; and, if the new data sample is determined to be added to a reservoir of data samples, sending a quality verification request to an oracle; receiving a new data sample quality estimate from the oracle; and adding the new data sample and estimate to the reservoir. A second aspect of the subject matter includes the actions of receiving, from a predictive model, a judgment associated with a new data sample; analyzing the new data sample based in part on the judgment to determine whether to send a new data sample quality verification request to an oracle; and, if a new data sample quality estimate is received from the oracle, determining whether to add the new data sample and the judgment to the reservoir.

Automated dynamic data quality assessment

Embodiments provide for automated dynamic data quality assessment. A data quality job including a new data sample is received. If the new data sample is determined to be added to a reservoir of data samples, a quality verification request is sent to an oracle. A new data sample quality estimate is received from the oracle. The new data sample and estimate can be added to the reservoir. A judgment associated with a new data sample is received from a predictive model. Whether to send a new data sample quality verification request to an oracle is determined. If a new data sample quality estimate is received from the oracle, whether to add the new data sample and the judgment to the reservoir is determined.

Automated adaptive data analysis using dynamic data quality assessment

In general, embodiments of the present invention provide systems, methods and computer readable media for an adaptive oracle-trained learning framework for automatically building and maintaining models that are developed using machine learning algorithms. In embodiments, the framework leverages at least one oracle (e.g., a crowd) for automatic generation of high-quality training data to use in deriving a model. Once a model is trained, the framework monitors the performance of the model and, in embodiments, leverages active learning and the oracle to generate feedback about the changing data for modifying training data sets while maintaining data quality to enable incremental adaptation of the model.

Processing dynamic data within an adaptive oracle-trained learning system using dynamic data set distribution optimization

Provided herein are systems, methods and computer readable media for identifying supply. An example for identifying merchants for fulfilling demand comprises receiving one or more virtual offers and an associated quantity of at least a portion of the one or more virtual offers, wherein the one or more virtual offers are representative of a residual demand for a geographic area, assigning a virtual offer of the one or more of the virtual offers to one or more merchants in an instance in which a supply source of the one or more merchants is identified as able to supply at least a portion of the associated quantity of the virtual offer, and determining a priority score for the one or more merchants, wherein the one or more merchants are rankable based on the priority score.

Method, apparatus, and computer program product for identification of supply sources

Provided herein are systems, methods and computer readable media for providing sales pipeline automation. An example method comprises calculating a forecasted demand, the forecasted demand comprising at least one or more virtual offers and a demanded quantity of at least a portion of the one or more virtual offers, identifying one or more merchants, wherein the one or more merchants are identified as able to supply at least a portion of the residual demand, assigning the one or more merchants to one or more sales resources in accordance with at least a calculated sales value of the one or more merchants.

Method, apparatus, and computer program product for sales pipeline automation

Automatic selection of high quality training data using an adaptive oracle-trained learning framework

Processing dynamic data within an adaptive oracle-trained learning system using curated training data for incremental re-training of a predictive model

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Burlingame, CA, United States of America

Shawn Ryan Jeffery