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MAICBR: A Multi-agent Intelligent Content-Based Recommendation System

Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 10)

Abstract

This study aims at proposing an intelligent and adaptive mechanism deploying intelligent agents for solving new user and overspecialization problems that exist in Content Based Recommendation (CBR) systems. Since the system is designed using software agents (SAs), it ensures highly desired full automation in web recommendations. The proposed system has been evaluated and the results suggested that there is an improvement in positive feedback rate and the decrease in recommendation rate.

Keywords

Content Ontology Overspecialization New user problem Recommendation Semantic Software agents 

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Copyright information

© Springer Nature Singapore Pte Ltd. 2018

Authors and Affiliations

  1. 1.MMICT & BMMaharishi Markandeshwer UniversityHaryanaIndia

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