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What is Model-Based Methods

Handbook of Research on Text and Web Mining Technologies
The process of learning the relationship model between the users and items given the user-item rating matrix.
Published in Chapter:
Collaborative Filtering Based Recommendation Systems
E. Thirumaran (Indian Institute of Science, India)
Copyright: © 2009 |Pages: 16
DOI: 10.4018/978-1-59904-990-8.ch040
Abstract
This chapter introduces Collaborative filtering-based recommendation systems, which has become an integral part of E-commerce applications, as can be observed in sites like Amazon.com. It will present several techniques that are reported in the literature to make useful recommendations, and study their limitations. The chapter also lists the issues that are currently open and the future directions that may be explored to address those issues. Furthermore, the authors hope that understanding of these limitations and issues will help build recommendation systems that are of high accuracy and have few false positive errors (which are products that are recommended, though the user does not like them).
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Foundational Recommender Systems for Business
As against neighborhood based methods, model based methods are formal supervised or unsupervised learning methods where a model has been established for prediction of test case.
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