An Intelligent Multi-agent Recommender System

2014 ◽  
pp. 201-213 ◽  
Author(s):  
Mahmood A. Mahmood ◽  
Nashwa El-Bendary ◽  
Jan Platoš ◽  
Aboul Ella Hassanien ◽  
Hesham A. Hefny
Keyword(s):  
Recommender System ◽  
Multi Agent

AVATAR: An Advanced Multi-agent Recommender System of Personalized TV Contents by Semantic Reasoning

2004 ◽  
pp. 415-421 ◽  
Author(s):  
Yolanda Blanco-Fernández ◽  
José J. Pazos-Arias ◽  
Alberto Gil-Solla ◽  
Manuel Ramos-Cabrer ◽  
Belén Barragáns-Martínez ◽  
...  
Keyword(s):  
Recommender System ◽  
Semantic Reasoning ◽  
Multi Agent

Aspect-Oriented Recommender Systems

2013 ◽  
pp. 55-72
Author(s):  
Punam Bedi ◽  
Sumit Kr Agarwal
Keyword(s):  
Decision Making ◽  
Recommender Systems ◽  
Recommender System ◽  
User Preference ◽  
Preference Learning ◽  
Decision Making Process ◽  
Design Issues ◽  
Aspect Oriented Programming ◽  
Multi Agent ◽  
Oriented Approach

Recommender systems are widely used intelligent applications which assist users in a decision-making process to choose one item amongst a potentially overwhelming set of alternative products or services. Recommender systems use the opinions of members of a community to help individuals in that community by identifying information most likely to be interesting to them or relevant to their needs. Recommender systems have various core design crosscutting issues such as: user preference learning, security, mobility, visualization, interaction etc that are required to be handled properly in order to implement an efficient, good quality and maintainable recommender system. Implementation of these crosscutting design issues of the recommender systems using conventional agent-oriented approach creates the problem of code scattering and code tangling. An Aspect-Oriented Recommender System is a multi agent system that handles core design issues of the recommender system in a better modular way by using the concepts of aspect oriented programming, which in turn improves the system reusability, maintainability, and removes the scattering and tangling problems from the recommender system.

scholarly journals Multi-Agent-Based CBR Recommender System for Intelligent Energy Management in Buildings

2019 ◽  
Vol 13 (1) ◽  
pp. 1084-1095 ◽  
Author(s):  
Tiago Pinto ◽  
Ricardo Faia ◽  
Maria Navarro-Caceres ◽  
Gabriel Santos ◽  
Juan Manuel Corchado ◽  
...  
Keyword(s):  
Energy Management ◽  
Recommender System ◽  
Agent Based ◽  
Multi Agent

Trust and reputation-based multi-agent recommender system

2018 ◽  
Vol 16 (4) ◽  
pp. 350 ◽  
Author(s):  
Punam Bedi ◽  
Sumit Kumar Agarwal ◽  
N.A. Richa
Keyword(s):  
Recommender System ◽  
Trust And Reputation ◽  
Multi Agent

A multi-agent legal recommender system

2008 ◽  
Vol 16 (2) ◽  
pp. 175-207 ◽  
Author(s):  
Lucas Drumond ◽  
Rosario Girardi
Keyword(s):  
Recommender System ◽  
Multi Agent

An intelligent location recommender system utilising multi-agent induced cognitive behavioural model

2020 ◽  
pp. 1-19
Author(s):  
Logesh Ravi ◽  
Malathi Devarajan ◽  
Vijayakumar V ◽  
Arun Kumar Sangaiah ◽  
Lipo Wang ◽  
...  
Keyword(s):  
Recommender System ◽  
Behavioural Model ◽  
Cognitive Behavioural ◽  
Multi Agent

Personal Tour

2012 ◽  
pp. 178-189
Author(s):  
Fabiana Lorenzi ◽  
Stanley Loh ◽  
Mara Abel
Keyword(s):  
Artificial Intelligence ◽  
Incomplete Information ◽  
Recommender System ◽  
Local Knowledge ◽  
Knowledge Bases ◽  
Distributed Artificial Intelligence ◽  
Multiple Agents ◽  
Multi Agent ◽  
User Recommendation

This chapter describes the Personal Tour: a multi-agent recommender system designed to help users to find best travel packages according to their preferences. Personal Tour is based on the collaboration of multiple agents exchanging information stored in their local knowledge bases. Based on the paradigm of the Distributed Artificial Intelligence, a user recommendation request is divided into partial recommendations handled by different agents, each one maintaining incomplete information that may be useful to compose a recommendation.

AVATAR: A Multi-Agent TV Recommender System using MHP Applications

2005 ◽  
Author(s):  
Y. Blanco-Fernandez ◽  
J.J. Pazos-Arias ◽  
A. Gil-Solla ◽  
M. Ramos-Cabrer ◽  
M. Lopez-Nores ◽  
...  
Keyword(s):  
Recommender System ◽  
Multi Agent
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