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What is Content-Based Recommender Systems

Encyclopedia of E-Business Development and Management in the Global Economy
Recommender systems that are based on content of items and recommend a list of items with similar content to that of the items that were given good feedback 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
Recommender Technologies and Emerging Applications
Recommender systems that are based on content of items and recommend a list of items with similar content to that of the items that were given good feedback by the target user.
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Personalized Recommendation: Approaches and Applications
Recommender systems that are based on content of items and recommend a list of items with similar content to that of the items that were given good feedback by the target consumer.
Full Text Chapter Download: US $37.50 Add to Cart
Content and Context-Aware Recommender Systems for Business
Content based systems work on data from users’ own ratings as well as attributes or features of the product to make recommendations by using unstructured data elements and applying NLP and other methods on the same.
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