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Journal of Applied Sciences
  Year: 2010 | Volume: 10 | Issue: 23 | Page No.: 3084-3090
DOI: 10.3923/jas.2010.3084.3090
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Improved Win-Win Quiescent Point Algorithm: A Recommender System Approach

A.A. Niknafs and H. Baghche Band

The aim of this study is introducing an online intelligent method for bidding negotiations in e-marketing. The growth and popularity of internet, increases using of modern techniques to help costumers and sellers in choosing best product and achieve higher benefit. Recommender systems as useful mean have memorable role in permanency customer loyalty. In traditional trade, customer and seller negotiate face to face. But now in online trade, it has changed to negotiation through internet and recommender systems. As a result, paying attention to preferences of both customer and seller in online structure is needed. In this study, we propose a method for making a recommender system for both seller and customer such that the satisfaction level of both be more than a threshold margin. First the needs and preferences of seller and customer are determined and then through the proposed algorithm successive suggestions are made until achieving a point that both sides of the business feel satisfaction.
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  •    Query Suggestion Generation Methods for Mobile Phones
  •    Interest Based Recommendations with Argumentation
  •    Recommender System Based on Collaborative Behavior of Ants
  •    An Agent-Based Framework for Building Decision Support System in Supply Chain Management
  •    A New Genetic Algorithm Recommender System for Achieving Customer-Seller Win-Win Quiescent Point
  •    A TAM Model to Evaluate User’s Attitude Towards Adoption of Decision Support Systems
How to cite this article:

A.A. Niknafs and H. Baghche Band, 2010. Improved Win-Win Quiescent Point Algorithm: A Recommender System Approach. Journal of Applied Sciences, 10: 3084-3090.

DOI: 10.3923/jas.2010.3084.3090






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