International Journal of Intelligent Information Systems

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A User Interest Model Based on the Analysis of User Behaviors

Received: 07 January 2015    Accepted: 10 January 2015    Published: 13 February 2015
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Abstract

Understanding the users' interest is the base for the industralization of website. In order to provide individualized service better for the users, on the basis of analyzing the users' browse behavioral characteristics and according to the users' retention time in the page, and users' click frequency to the hyperlink and page, a model of computer user interest degree is established, and a neutral network is proposed to describe their correlation, and the reasonableness and effectiveness of this model are verified through experiment. The experiemtn result shows aathat this model can accurately find out the page that the users are interested in.

DOI 10.11648/j.ijiis.s.2015040202.12
Published in International Journal of Intelligent Information Systems (Volume 4, Issue 2-2, March 2015)

This article belongs to the Special Issue Content-based Image Retrieval and Machine Learning

Page(s) 5-8
Creative Commons

This is an Open Access article, distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution and reproduction in any medium or format, provided the original work is properly cited.

Copyright

Copyright © The Author(s), 2024. Published by Science Publishing Group

Keywords

Individualization, User Browse Behavior, User Interest Degree, RBF Network

References
[1] Enrique Frias-Martinez, Sherry Y. Chen, Xiaohui Liu. Investigation of Behavior and Perception of Digital Library Users: A Cognitive Style Perspective[J]. International Journal of Information Management , 2008(28): 355-365.
[2] Zhang Haitao, Jing Jipeng, Method of Determining Webpage Level According to User Browse Behavior [J]. Intelligence Journal, 2004, 23(3): 303-306.
[3] Cheng Chih Chang, Pei-Ling Chen, Fei-Rung Chiu, et al. Application of Neural Networks and Kano’s Method to Content Recommendation in Web Personalization[J]. Expert Systems with Applications, 2008.
[4] A. Georgakis, H. Li. User Behavior Modeling and Content Based Speculative Web Page Prefetching[J]. Data & Knowledge Engineering, 2006(59): 770-788.
[5] Wang Jimin, Peng Bo, Analysis on Click Behavior of Search Engine Users [J]. Intelligence Journal, 2006(2): 154-162.
[6] Feng-Hsu Wang, Hsiu-Mei Shao. Effective Personalized Recommendation Based on Time-Framed Navigation Clustering and Association Mining [J]. Expert Systems with Applications, 2004(27): 365-377.
[7] Mrugank V Thakor, Wendy Borsuk, Maria Kalamas. Hotlists and Web Browsing Behavior - an Empirical Investigation [J]. Journal of Business Research, 2004(57): 776-786.
[8] Zeng Chun, Xing Chunxiao, Zhou Lizhu, Technical Overview of Individualized Service [J]. Software Journal , 2002(10): 1952-1961.
[9] Shuchih Emest Changa, S Wesley Changchiena. Assessing Users’ Product-Specific Knowledge for Personalization[J]. Expert Systems with Applications, 2006(30): 682-693.
[10] Shu-Hsien Liao, Chih-Hao Wen, Artificial Neural Networks Classification and Clustering of Methodologies and Applications Literature Analysis From 1995 to 2005[J]. Expert Systems with Applications, 2007(32): 1-11.
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Author Information
  • College of Network Communication, Zhejiang Yuexiu University of Foreign Languages, Shaoxing, China

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  • APA Style

    Zhu Jinghua. (2015). A User Interest Model Based on the Analysis of User Behaviors. International Journal of Intelligent Information Systems, 4(2-2), 5-8. https://doi.org/10.11648/j.ijiis.s.2015040202.12

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    ACS Style

    Zhu Jinghua. A User Interest Model Based on the Analysis of User Behaviors. Int. J. Intell. Inf. Syst. 2015, 4(2-2), 5-8. doi: 10.11648/j.ijiis.s.2015040202.12

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    AMA Style

    Zhu Jinghua. A User Interest Model Based on the Analysis of User Behaviors. Int J Intell Inf Syst. 2015;4(2-2):5-8. doi: 10.11648/j.ijiis.s.2015040202.12

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  • @article{10.11648/j.ijiis.s.2015040202.12,
      author = {Zhu Jinghua},
      title = {A User Interest Model Based on the Analysis of User Behaviors},
      journal = {International Journal of Intelligent Information Systems},
      volume = {4},
      number = {2-2},
      pages = {5-8},
      doi = {10.11648/j.ijiis.s.2015040202.12},
      url = {https://doi.org/10.11648/j.ijiis.s.2015040202.12},
      eprint = {https://download.sciencepg.com/pdf/10.11648.j.ijiis.s.2015040202.12},
      abstract = {Understanding the users' interest is the base for the industralization of website. In order to provide individualized service better for the users, on the basis of analyzing the users' browse behavioral characteristics and according to the users' retention time in the page, and users' click frequency to the hyperlink and page, a model of computer user interest degree is established, and a neutral network is proposed to describe their correlation, and the reasonableness and effectiveness of this model are verified through experiment. The experiemtn result shows aathat this model can accurately find out the page that the users are interested in.},
     year = {2015}
    }
    

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  • TY  - JOUR
    T1  - A User Interest Model Based on the Analysis of User Behaviors
    AU  - Zhu Jinghua
    Y1  - 2015/02/13
    PY  - 2015
    N1  - https://doi.org/10.11648/j.ijiis.s.2015040202.12
    DO  - 10.11648/j.ijiis.s.2015040202.12
    T2  - International Journal of Intelligent Information Systems
    JF  - International Journal of Intelligent Information Systems
    JO  - International Journal of Intelligent Information Systems
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    UR  - https://doi.org/10.11648/j.ijiis.s.2015040202.12
    AB  - Understanding the users' interest is the base for the industralization of website. In order to provide individualized service better for the users, on the basis of analyzing the users' browse behavioral characteristics and according to the users' retention time in the page, and users' click frequency to the hyperlink and page, a model of computer user interest degree is established, and a neutral network is proposed to describe their correlation, and the reasonableness and effectiveness of this model are verified through experiment. The experiemtn result shows aathat this model can accurately find out the page that the users are interested in.
    VL  - 4
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    ER  - 

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