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.


Full Text: PDF DOI: 10.5539/mas.v6n6p39

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This work is licensed under a Creative Commons Attribution 3.0 License.

Modern Applied Science   ISSN 1913-1844 (Print)   ISSN 1913-1852 (Online)

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