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The Teaching Resources Recommendation System Research Based on Java EE

Received: 20 April 2016     Published: 21 April 2016
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Abstract

With the growing popularity of teaching resources platform construction, various forms of teaching resource materials more and more, how to provide users with intelligent recommendation of teaching resources is a key issue. This article will be introduced to the trust relationship neighbor recommended an improved algorithm recommendation algorithm, designed to ease cold start recommendation system, we recommend that affect the process of distrust. The recommendation that the improved algorithm is applied to Java EE-based teaching resource recommendation system, effectively improve the system of teaching resources recommended to the user efficiency and accuracy, improve the real-time requirements so that online learning system.

Published in Software Engineering (Volume 4, Issue 2)
DOI 10.11648/j.se.20160402.13
Page(s) 19-26
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), 2016. Published by Science Publishing Group

Keywords

Trusts, Recommended Neighbor Algorithm, Java EE

References
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[4] JCP Expert Group. JSR-244 (Java EE. O) [S/OL]. http://jcp.org/en/jsr/detail?id=244.
[5] T. C. Wang, The design and implementation of online examination system based on Java EE, [D], South China University of Technology, 2014(5), pp. 6-8.
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[7] H. M. Li, EJB3. 0 Introduction to the classic, [M], Tsinghua university press, 2009.
[8] J. Cu, Based on the radio and television university comprehensive practice link of Java EE, [J] Jilin university, 2011, pp. 16-18.
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Cite This Article
  • APA Style

    Haihui Wu, Bo Song. (2016). The Teaching Resources Recommendation System Research Based on Java EE. Software Engineering, 4(2), 19-26. https://doi.org/10.11648/j.se.20160402.13

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    ACS Style

    Haihui Wu; Bo Song. The Teaching Resources Recommendation System Research Based on Java EE. Softw. Eng. 2016, 4(2), 19-26. doi: 10.11648/j.se.20160402.13

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    AMA Style

    Haihui Wu, Bo Song. The Teaching Resources Recommendation System Research Based on Java EE. Softw Eng. 2016;4(2):19-26. doi: 10.11648/j.se.20160402.13

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  • @article{10.11648/j.se.20160402.13,
      author = {Haihui Wu and Bo Song},
      title = {The Teaching Resources Recommendation System Research Based on Java EE},
      journal = {Software Engineering},
      volume = {4},
      number = {2},
      pages = {19-26},
      doi = {10.11648/j.se.20160402.13},
      url = {https://doi.org/10.11648/j.se.20160402.13},
      eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.se.20160402.13},
      abstract = {With the growing popularity of teaching resources platform construction, various forms of teaching resource materials more and more, how to provide users with intelligent recommendation of teaching resources is a key issue. This article will be introduced to the trust relationship neighbor recommended an improved algorithm recommendation algorithm, designed to ease cold start recommendation system, we recommend that affect the process of distrust. The recommendation that the improved algorithm is applied to Java EE-based teaching resource recommendation system, effectively improve the system of teaching resources recommended to the user efficiency and accuracy, improve the real-time requirements so that online learning system.},
     year = {2016}
    }
    

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  • TY  - JOUR
    T1  - The Teaching Resources Recommendation System Research Based on Java EE
    AU  - Haihui Wu
    AU  - Bo Song
    Y1  - 2016/04/21
    PY  - 2016
    N1  - https://doi.org/10.11648/j.se.20160402.13
    DO  - 10.11648/j.se.20160402.13
    T2  - Software Engineering
    JF  - Software Engineering
    JO  - Software Engineering
    SP  - 19
    EP  - 26
    PB  - Science Publishing Group
    SN  - 2376-8037
    UR  - https://doi.org/10.11648/j.se.20160402.13
    AB  - With the growing popularity of teaching resources platform construction, various forms of teaching resource materials more and more, how to provide users with intelligent recommendation of teaching resources is a key issue. This article will be introduced to the trust relationship neighbor recommended an improved algorithm recommendation algorithm, designed to ease cold start recommendation system, we recommend that affect the process of distrust. The recommendation that the improved algorithm is applied to Java EE-based teaching resource recommendation system, effectively improve the system of teaching resources recommended to the user efficiency and accuracy, improve the real-time requirements so that online learning system.
    VL  - 4
    IS  - 2
    ER  - 

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Author Information
  • College of Software, Shenyang Normal University, Liaoning Shenyang, China

  • College of Software, Shenyang Normal University, Liaoning Shenyang, China

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