An Improved Ontology-Based User Interest Model


  •  Zhu Liang    
  •  Yan Jun    
  •  Ling Haifeng    
  •  Qian Haibo    

Abstract

In the personalized information retrieval, the design of user interest model is a key problem. Through analyzing the Ontology-based User Interest Model, propose a new hybrid model that contains both long-term and short-term model, and the long-term model updated from Vector Space Model by transform algorithm. Experiments showed that the new model tracked user’s interests more accurately, and greatly avoided the Cold Start problem.



This work is licensed under a Creative Commons Attribution 4.0 License.
  • ISSN(Print): 1913-1844
  • ISSN(Online): 1913-1852
  • Started: 2007
  • Frequency: monthly

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