AKNOBAS: A Knowledge-based Segmentation Recommender System based on Intelligent Data Mining Techniques

作者：Rodriguez Gonzalez Alejandro^*; Torres Nino Javier; Jimenez Domingo Enrique; Miguel Gomez Berbis Juan; Alor Hernandez Giner

来源：Computer Science and Information Systems, 2012, 9(2): 713-740.

DOI：10.2298/CSIS110722008R

• Data Mining
• Clustering
• Information Systems
• Artificial Intelligence
• Use Case

Recommender Systems have recently undergone an unwavering improvement in terms of efficiency and pervasiveness. They have become a source of competitive advantage in many companies which thrive on them as the technological core of their business model. In recent years, we have made substantial progress in those Recommender Systems outperforming the accuracy and added-value of their predecessors, by using cutting-edge techniques such as Data Mining and Segmentation. In this paper, we present AKNOBAS, a Knowledge-based Segmentation Recommender System, which follows that trend using Intelligent Clustering Techniques for Information Systems. The contribution of this Recommender System has been validated through a business scenario implementation proof-of-concept and provides a clear breakthrough of marshaling information through AI techniques.

• 出版日期2012-6