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US008037080B2 (12) Bulleted States Patent (10) Patent N0.: Korea (54) US 8,037,080 B2 (45) Date of Patent: RECOMMENDER SYSTEM UTILIZING 2004/0260574 A1 COLLABORATIVE FILTERING COMBINING 2 EXPLICIT

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What is recommender system utilizing collaborative?

A recommender system utilizing collaborative filtering is a type of recommendation system that uses the preferences and behaviors of a group of users to make personalized recommendations to individuals. It works by identifying similarities between users based on their past interactions and then suggesting items that were liked by other similar users.

Who is required to file recommender system utilizing collaborative?

There is no specific requirement to file a recommender system utilizing collaborative. It is a technology or algorithm used by various platforms and applications to provide personalized recommendations to their users.

How to fill out recommender system utilizing collaborative?

A recommender system utilizing collaborative filtering is typically implemented by developers or data scientists using programming languages such as Python or R. It involves collecting and analyzing user data, building a similarity matrix, and developing an algorithm to generate personalized recommendations based on this data.

What is the purpose of recommender system utilizing collaborative?

The purpose of a recommender system utilizing collaborative filtering is to provide personalized recommendations to users based on their past behaviors and preferences, as well as the behaviors and preferences of similar users. This helps improve user satisfaction and engagement, increases sales and conversions, and enhances the user experience.

What information must be reported on recommender system utilizing collaborative?

There is no specific information that needs to be reported on a recommender system utilizing collaborative filtering. The system itself analyzes user data and generates recommendations based on that data, without requiring any additional reporting.

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