11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness

Research Article

Towards A Hybrid Approach of Primitive Cognitive Network Process and Agglomerative Hierarchical Clustering for Music Recommendation

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  • @INPROCEEDINGS{10.4108/eai.19-8-2015.2261344,
        author={Chun Guan and Kevin Kam Fung Yuen},
        title={Towards A Hybrid Approach of Primitive Cognitive Network Process and Agglomerative Hierarchical Clustering for Music Recommendation},
        proceedings={11th EAI International Conference on Heterogeneous Networking for Quality, Reliability, Security and Robustness},
        publisher={IEEE},
        proceedings_a={QSHINE},
        year={2015},
        month={9},
        keywords={primitive cognitive network process hierarchical clustering recommendation system},
        doi={10.4108/eai.19-8-2015.2261344}
    }
    
  • Chun Guan
    Kevin Kam Fung Yuen
    Year: 2015
    Towards A Hybrid Approach of Primitive Cognitive Network Process and Agglomerative Hierarchical Clustering for Music Recommendation
    QSHINE
    IEEE
    DOI: 10.4108/eai.19-8-2015.2261344
Chun Guan1, Kevin Kam Fung Yuen2,*
  • 1: University of Liverpool
  • 2: Xi'an Jiaotong-Liverpool University
*Contact email: kevinkf.yuen@gmail.com

Abstract

Clustering algorithms have been used in many real world applications including recommendation systems. This paper proposes PCNP-AHC, which is a hybrid approach of Primitive Cognitive Network Process (PCNP) and Agglomerative Hierarchical Clustering (AHC) to cluster music pieces on the basis of user’s preferences and similarities between music pieces. PCNP is an ideal alternative of Analytic Hierarchy Process (AHP) to quantify weights of attributes which are used in clustering process. The application of PCNP-AHC for music recommendation is demonstrated.