Yahoo Assets LLC

Oath Inc.

Verizon Media Inc.

Umang Patel

Rofaida Abdelaal

Chun-Han Yao

Sridharan Palaniappan

Ariel Raviv

Dotan Di Castro

Ian McCarthy

Ariella Voloshin

Kenneth Sebastian

Ariel Livshits

Irena Grabovitch

The present teaching relates to method, system, medium, and implementations for product recommendation. When communication content is received from a service provider operating on a platform, information related to a product is identified from a webpage accessed based on a link included in the communication content. Based on the information related to the product, a recommendation of the product is generated and sent to some service providers on different platforms for distribution of the recommendation to intended targets.

System and method for automated recommendation generation from communication content and application thereof

Disclosed are systems and methods for extracting content based on image analysis. A method may include receiving content including at least an image depicting a coupon; converting the received content into a larger image including the image depicting the coupon; determining, utilizing one or more neural networks, the image depicting the coupon within the larger image, wherein determining the image depicting the coupon comprises: segmenting a foreground bounding box including the image depicting the coupon from background image portions of the image; cropping the larger image based on the bounding box, wherein the cropped image consists of the image depicting the coupon; determining text included in the cropped image; and extracting information included in the coupon based on the determined text.

Systems and methods for deep learning based approach for content extraction

Disclosed are systems and methods for improving interactions with and between computers in content providing, searching and/or hosting systems supported by or configured with devices, servers and/or platforms. The disclosed systems and methods provide a novel framework for partitioning HTML content in electronic messages based on the relative positions of the content's links within the DOM hierarchy of the messages, and basing the propagation (e.g., display or communication) of such content therefrom. The disclosed message partitioning and extraction framework can be applied online, in real-time, at scale, without any pre-processing or pre-learning/training.

Computerized system and method for digital content extraction and propagation in HTML messages

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Sunnyvale, CA, United States of America

Umang Patel