A Fuzzy Ontology Framework Based on User Profile

Jingfeng Shao; Xiaoyu Yang; Chuangtao Ma

doi:doi:10.11648/j.edu.20170605.12

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A Fuzzy Ontology Framework Based on User Profile

Jingfeng Shao, Xiaoyu Yang, Chuangtao Ma

Published in Education Journal (Volume 6, Issue 5)

Received: 23 October 2017 Accepted: Published: 27 October 2017

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Abstract

Aimed at the problem of the classical ontology cannot represent the imprecision and uncertainty information, firstly, the ambiguity and uncertainty of fuzzy information was analyzed, and the fuzzy concept relationship was expressed by using fuzzy membership function. And then, the user interest estimation based on behavior was studied in term of user’s learning preferences, and user profile was described by the learning object, Furthermore, fuzzy ontology under different granularity was built, the fuzzy concept lattice was clustered, and the concept similarity of fuzzy formal concepts was calculated. Finally, a fuzzy ontology framework based on user profile was proposed. As verified by experiment, the results have shown that the framework can reduce efficiently the uncertainty information of fuzzy ontology, and enhance the precision of ontology.

Published in	Education Journal (Volume 6, Issue 5)
DOI	10.11648/j.edu.20170605.12
Page(s)	152-158
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

Ontology Framework, User Profile, Similarity Degree, Fuzzy Ontology

References

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APA Style

Jingfeng Shao, Xiaoyu Yang, Chuangtao Ma. (2017). A Fuzzy Ontology Framework Based on User Profile. Education Journal, 6(5), 152-158. https://doi.org/10.11648/j.edu.20170605.12

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ACS Style

Jingfeng Shao; Xiaoyu Yang; Chuangtao Ma. A Fuzzy Ontology Framework Based on User Profile. Educ. J. 2017, 6(5), 152-158. doi: 10.11648/j.edu.20170605.12

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AMA Style

Jingfeng Shao, Xiaoyu Yang, Chuangtao Ma. A Fuzzy Ontology Framework Based on User Profile. Educ J. 2017;6(5):152-158. doi: 10.11648/j.edu.20170605.12

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@article{10.11648/j.edu.20170605.12,
  author = {Jingfeng Shao and Xiaoyu Yang and Chuangtao Ma},
  title = {A Fuzzy Ontology Framework Based on User Profile},
  journal = {Education Journal},
  volume = {6},
  number = {5},
  pages = {152-158},
  doi = {10.11648/j.edu.20170605.12},
  url = {https://doi.org/10.11648/j.edu.20170605.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20170605.12},
  abstract = {Aimed at the problem of the classical ontology cannot represent the imprecision and uncertainty information, firstly, the ambiguity and uncertainty of fuzzy information was analyzed, and the fuzzy concept relationship was expressed by using fuzzy membership function. And then, the user interest estimation based on behavior was studied in term of user’s learning preferences, and user profile was described by the learning object, Furthermore, fuzzy ontology under different granularity was built, the fuzzy concept lattice was clustered, and the concept similarity of fuzzy formal concepts was calculated. Finally, a fuzzy ontology framework based on user profile was proposed. As verified by experiment, the results have shown that the framework can reduce efficiently the uncertainty information of fuzzy ontology, and enhance the precision of ontology.},
 year = {2017}
}

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TY  - JOUR
T1  - A Fuzzy Ontology Framework Based on User Profile
AU  - Jingfeng Shao
AU  - Xiaoyu Yang
AU  - Chuangtao Ma
Y1  - 2017/10/27
PY  - 2017
N1  - https://doi.org/10.11648/j.edu.20170605.12
DO  - 10.11648/j.edu.20170605.12
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
SP  - 152
EP  - 158
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20170605.12
AB  - Aimed at the problem of the classical ontology cannot represent the imprecision and uncertainty information, firstly, the ambiguity and uncertainty of fuzzy information was analyzed, and the fuzzy concept relationship was expressed by using fuzzy membership function. And then, the user interest estimation based on behavior was studied in term of user’s learning preferences, and user profile was described by the learning object, Furthermore, fuzzy ontology under different granularity was built, the fuzzy concept lattice was clustered, and the concept similarity of fuzzy formal concepts was calculated. Finally, a fuzzy ontology framework based on user profile was proposed. As verified by experiment, the results have shown that the framework can reduce efficiently the uncertainty information of fuzzy ontology, and enhance the precision of ontology.
VL  - 6
IS  - 5
ER  -

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Author Information

Jingfeng Shao

School of Management, Xi’an Polytechnic University, Xi’an, China
Xiaoyu Yang

School of Management, Xi’an Polytechnic University, Xi’an, China
Chuangtao Ma

School of Management, Xi’an Polytechnic University, Xi’an, China

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APA Style

Jingfeng Shao, Xiaoyu Yang, Chuangtao Ma. (2017). A Fuzzy Ontology Framework Based on User Profile. Education Journal, 6(5), 152-158. https://doi.org/10.11648/j.edu.20170605.12

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ACS Style

Jingfeng Shao; Xiaoyu Yang; Chuangtao Ma. A Fuzzy Ontology Framework Based on User Profile. Educ. J. 2017, 6(5), 152-158. doi: 10.11648/j.edu.20170605.12

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AMA Style

Jingfeng Shao, Xiaoyu Yang, Chuangtao Ma. A Fuzzy Ontology Framework Based on User Profile. Educ J. 2017;6(5):152-158. doi: 10.11648/j.edu.20170605.12

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@article{10.11648/j.edu.20170605.12,
  author = {Jingfeng Shao and Xiaoyu Yang and Chuangtao Ma},
  title = {A Fuzzy Ontology Framework Based on User Profile},
  journal = {Education Journal},
  volume = {6},
  number = {5},
  pages = {152-158},
  doi = {10.11648/j.edu.20170605.12},
  url = {https://doi.org/10.11648/j.edu.20170605.12},
  eprint = {https://article.sciencepublishinggroup.com/pdf/10.11648.j.edu.20170605.12},
  abstract = {Aimed at the problem of the classical ontology cannot represent the imprecision and uncertainty information, firstly, the ambiguity and uncertainty of fuzzy information was analyzed, and the fuzzy concept relationship was expressed by using fuzzy membership function. And then, the user interest estimation based on behavior was studied in term of user’s learning preferences, and user profile was described by the learning object, Furthermore, fuzzy ontology under different granularity was built, the fuzzy concept lattice was clustered, and the concept similarity of fuzzy formal concepts was calculated. Finally, a fuzzy ontology framework based on user profile was proposed. As verified by experiment, the results have shown that the framework can reduce efficiently the uncertainty information of fuzzy ontology, and enhance the precision of ontology.},
 year = {2017}
}

Copy | Download

TY  - JOUR
T1  - A Fuzzy Ontology Framework Based on User Profile
AU  - Jingfeng Shao
AU  - Xiaoyu Yang
AU  - Chuangtao Ma
Y1  - 2017/10/27
PY  - 2017
N1  - https://doi.org/10.11648/j.edu.20170605.12
DO  - 10.11648/j.edu.20170605.12
T2  - Education Journal
JF  - Education Journal
JO  - Education Journal
SP  - 152
EP  - 158
PB  - Science Publishing Group
SN  - 2327-2619
UR  - https://doi.org/10.11648/j.edu.20170605.12
AB  - Aimed at the problem of the classical ontology cannot represent the imprecision and uncertainty information, firstly, the ambiguity and uncertainty of fuzzy information was analyzed, and the fuzzy concept relationship was expressed by using fuzzy membership function. And then, the user interest estimation based on behavior was studied in term of user’s learning preferences, and user profile was described by the learning object, Furthermore, fuzzy ontology under different granularity was built, the fuzzy concept lattice was clustered, and the concept similarity of fuzzy formal concepts was calculated. Finally, a fuzzy ontology framework based on user profile was proposed. As verified by experiment, the results have shown that the framework can reduce efficiently the uncertainty information of fuzzy ontology, and enhance the precision of ontology.
VL  - 6
IS  - 5
ER  -

Copy | Download