Intelligent Product Brokering and User Preference Tracking

2004 ◽  
pp. 166-185
Author(s):  
Sheng-Uei Guan ◽  
Chon Seng Ngoo ◽  
Fangming Zhu
Keyword(s):  
Genetic Algorithms ◽  
Potential Application ◽  
User Preference ◽  
Evaluation Function ◽  
Agent Based ◽  
Evolutionary Ontology ◽  
Intelligent Product ◽  
Current Systems

One potential application for agent-based systems has been in the area of m-commerce. In most current systems, user-supplied keywords are normally used to generate a profile for the user. In this chapter, a design for an evolutionary ontology-based product-brokering agent for m-commerce applications is proposed. It uses an evaluation function to represent the user’s preference instead of the usual keyword-based profile. By using genetic algorithms, the agent tries to track the user’s preferences for a particular product by tuning some parameters inside. A prototype was implemented in Java, and the results obtained from our experiments look promising.

Intelligent Product Brokering Services

2011 ◽  
pp. 527-543
Author(s):  
Sheng-Uei Guan
Keyword(s):  
Genetic Algorithms ◽  
Evaluation Function ◽  
Agent Based ◽  
Evolutionary Ontology ◽  
Intelligent Product

Agent-based system has great potential in the area of m-commerce and a lot of research has been done on making the system intelligent enough to personalize its service for users. In most systems, user-supplied keywords are normally used to generate a profile for each user. In this chapter, a design for an evolutionary ontology-based product-brokering agent for m-commerce applications has been proposed. It uses an evaluation function to represent the user’s preference instead of the usual keyword-based profile. By using genetic algorithms, the agent tries to track the user’s preferences for a particular product by tuning some of the parameters inside this function. A Java-based prototype has been implemented and the results obtained from our experiments look promising.

scholarly journals Optimization of HAART with genetic algorithms and agent-based models of HIV infection

2007 ◽  
Vol 23 (24) ◽  
pp. 3350-3355 ◽  
Author(s):  
F. Castiglione ◽  
F. Pappalardo ◽  
M. Bernaschi ◽  
S. Motta
Keyword(s):  
Genetic Algorithms ◽  
Hiv Infection ◽  
Agent Based Models ◽  
Agent Based

Parallel Multi-Criterion Genetic Algorithms

2016 ◽  
pp. 172-186
Author(s):  
Bhabani Shankar Prasad Mishra ◽  
Subhashree Mishra ◽  
Sudhansu Sekhar Singh
Keyword(s):  
Genetic Algorithm ◽  
Genetic Algorithms ◽  
Potential Application ◽  
Processing Time ◽  
Acceptable Solution ◽  
Multi Objective ◽  
Multi Objective Genetic Algorithm

The objective of this paper is to study the existing and current research on parallel multi-objective genetic algorithms (PMOGAs) through an intensive experiment. Many early efforts on parallelizing multi-objective genetic algorithms were introduced to reduce the processing time needed to reach an acceptable solution of them with various examples. Further, the authors tried to identify some of the issues that have not yet been studied systematically under the umbrella of parallel multi-objective genetic algorithms. Finally, some of the potential application of parallel multi objective genetic algorithm is discussed.

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