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What is User-to-User Collaborative Filtering

Encyclopedia of E-Business Development and Management in the Global Economy
Collaborative method that is based on similar consumers and recommends a list of items that other consumer gave feedback similar to that provided by the target consumer.
Published in Chapter:
Recommender Systems: An Overview
Young Park (Bradley University, USA)
DOI: 10.4018/978-1-61520-611-7.ch123
Abstract
With the explosive growth of goods and services available on the Web through e-commerce, it is increasingly difficult for consumers to find the right products or services. Recommender systems provide consumers with personalized recommendations of goods or services and thus help them find relevant goods or services in the information overload. Since they were introduced a decade ago, recommendation technologies have made significant progress. This article presents a brief overview of recommender systems as an effective and powerful personalization tool in the e-commerce environment. Current major recommendation approaches are described and reviewed within a single unifying recommendation model and future directions are also discussed. Recommender systems and technologies will continue to have an essential role in future e-commerce and e-business.
Full Text Chapter Download: US $37.50 Add to Cart
More Results
Personalized Recommendation: Approaches and Applications
Collaborative method that is based on similar consumers and recommends a list of items that other consumer gave feedback similar to that provided by the target consumer.
Full Text Chapter Download: US $37.50 Add to Cart
Recommender Technologies and Emerging Applications
Collaborative filtering method that is based on similar users and recommends a list of items that other user gave relevance feedback similar to that provided by the target user.
Full Text Chapter Download: US $37.50 Add to Cart
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