Abstract
In B2B e-Marketplace for free gifts and goods, product-mix recommendation is provided frequently by analysing customer logs and/or performing collaborative and rules-based filtering. This study proposes a new process that encompasses the genetic algorithm and key working processes of B2B e-marketplace based on the previous cooperate client order data. Efficiency and accuracy of the proposed system have been confirmed by crossconfirmation of accumulated data in the e-marketplace. The system can provide better opportunities for manufactures and suppliers to select optimized product-mix without time consuming trials and errors in their B2B e-marketplace networks
| Translated title of the contribution | An Implementation of the B2B e-Marketplace Product Recommendation System using Genetic Algorithm |
|---|---|
| Original language | Korean |
| Pages (from-to) | 135-142 |
| Number of pages | 8 |
| Journal | 대한산업공학회지 |
| Volume | 39 |
| Issue number | 2 |
| DOIs | |
| State | Published - Apr 2013 |