NAVE BAYESIAN CLASSIFIERBASED PRIVATE RECOMMENDATIONS: PRIVACYPRESERVING NAVE BAYESIAN CLASSIFIERBASED COLLABORATIVE FILTERIN,Used

NAVE BAYESIAN CLASSIFIERBASED PRIVATE RECOMMENDATIONS: PRIVACYPRESERVING NAVE BAYESIAN CLASSIFIERBASED COLLABORATIVE FILTERIN,Used

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SKU: DADAX3838347722
Brand: LAP Lambert Academic Publishing
Condition: New
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Collaborative filtering (CF) has become very popular on the Internet. Although CF systems are widely used, they have various challenges in recommendation process. For better results, such systems need quality data; however, due to privacy concerns, users hesitate to send their private data or they might send false data. CF systems provide referrals on existing databases compromised of ratings recorded from groups of people evaluating various items; sometimes, the systems? ratings might be split among different parties. The parties may wish to share their data; but they may not want to disclose their data. Online computation time increases with augmenting number of users. In this book, approaches are proposed to overcome challenges for nave Bayesian classifier (NBC)based CF algorithm. A new scheme is proposed to produce NBCbased recommendations while preserving users? privacy by utilizing randomized response techniques (RRT). To offer CF services on distributed data between two parties without violating their privacy, solutions are provided. And finally, a method is proposed for optimizing privacypreserving NBCbased CF scheme using kmodes clustering.

⚠️ WARNING (California Proposition 65):

This product may contain chemicals known to the State of California to cause cancer, birth defects, or other reproductive harm.

For more information, please visit www.P65Warnings.ca.gov.

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