17878845. PRODUCT IDENTIFICATION IN MEDIA ITEMS simplified abstract (GOOGLE LLC)

PRODUCT IDENTIFICATION IN MEDIA ITEMS

Organization Name

GOOGLE LLC

Inventor(s)

Marco Ziccardi of Basel (CH)

Min-hsuan Tsai of San Jose CA (US)

Wei-Hong Chuang of Palo Alto CA (US)

Rahul Sunil Bhalerao of Sunnyvale CA (US)

Ye Xia of Santa Clara CA (US)

Madhuri Shanbhogue of San Jose CA (US)

Mojtaba Seyedhosseini of Foster City CA (US)

Mike Krainin of Arlington MA (US)

Andrei Kapishnikov of Watertown MA (US)

Yuanzhen Li of Newton MA (US)

PRODUCT IDENTIFICATION IN MEDIA ITEMS - A simplified explanation of the abstract

This abstract first appeared for US patent application 17878845 titled 'PRODUCT IDENTIFICATION IN MEDIA ITEMS

Simplified Explanation

The method described in the patent application involves using machine learning to determine the accuracy of product identifiers associated with content items. Here are the key points:

• Obtaining first data, including a first identifier of a first product, associated with a content item based on first metadata of the content item.
• Obtaining a first confidence value associated with the first product and the content item.
• Obtaining second data, including a second identifier of the first product and a second confidence value.
• Providing the first data and the second data to a trained machine learning model.
• Obtaining a third confidence value from the trained machine learning model associated with the first product.
• Adjusting second metadata of the content item based on the third confidence value.

Potential applications of this technology:

• E-commerce platforms can use this method to improve the accuracy of product identification and enhance the user experience.
• Content creators and publishers can utilize this method to ensure the correct product information is associated with their content.
• Online marketplaces can benefit from this technology by reducing errors in product listings and improving search results.

Problems solved by this technology:

• Inaccurate product identification can lead to incorrect information being associated with content items, resulting in a poor user experience.
• Manual verification of product identifiers can be time-consuming and prone to errors.
• Ensuring the accuracy of product information is crucial for e-commerce platforms and online marketplaces to maintain customer trust and satisfaction.

Benefits of this technology:

• Improved accuracy in product identification enhances the relevance and reliability of content items.
• Automation of the verification process saves time and reduces human error.
• Enhanced user experience leads to increased customer satisfaction and potentially higher sales for e-commerce platforms and online marketplaces.

Original Abstract Submitted

A method includes obtaining first data including a first identifier of a first product determine in association with a content item based on first metadata of the content item. The method further includes obtaining a first confidence value associated with the first product and the content item. The method further includes obtaining second data including a second identifier of the first product and a second confidence value. The method further includes providing the first data and the second data to a trained machine learning model. The method further includes obtaining a third confidence value from the trained machine learning model associated with the first product. The method further includes adjusting second metadata of the content item in view of the third confidence value.