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

被引:6
作者
Rodriguez-Gonzalez, Alejandro [1 ]
Torres-Nino, Javier [1 ]
Jimenez-Domingo, Enrique [1 ]
Miguel Gomez-Berbis, Juan [1 ]
Alor-Hernandez, Giner [2 ]
机构
[1] Univ Carlos III Madrid, Dept Comp Sci, Madrid 28911, Spain
[2] Inst Tecnol Orizaba, Div Res & Postgrad Studies, Orizaba 94320, Veracruz, Mexico
关键词
Data Mining; Clustering; Information Systems; Artificial Intelligence; Use Case;
D O I
10.2298/CSIS110722008R
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
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.
引用
收藏
页码:713 / 740
页数:28
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