A Fuzzy Ontology Framework Based on User Profile

Jingfeng Shao; Xiaoyu Yang; Chuangtao Ma

doi:doi:10.11648/j.edu.20170605.12

| Peer-Reviewed

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 Published: 27 October 2017

Views: Downloads:

Download PDF

Share This Article

Twitter
Linked In
Facebook

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), 2017. Published by Science Publishing Group

Keywords

Ontology Framework, User Profile, Similarity Degree, Fuzzy Ontology

References

[1]	Gruber T. Translation Approach to Portable ontology Specifications, Knowledge Acquisition 1993, (5):199-220.
[2]	Borst W N. Construction of Engineering Ontologies for Knowledge Sharing and Reuse [D]. Ph.D. Thesis, University of Twente, Enschede, 1997.
[3]	Kang X P, Li D Y, Wang S G, et al. Formal Concept Analysis Based on Fuzzy Granularity base for Different Granulations [J]. Fuzzy Sets and Systems, 2012, (30):120-125.
[4]	Atanassov K. Remarks on the Intuitionistic Fuzzy Sets III [J]. Fuzzy Sets and Systems, 1995, 75 (3):401-402.
[5]	Jiang Y C, Tang Y, Wang J, et al. Representation and Reasoning of Context-dependant Knowledge in Distributed Fuzzy Ontologies [J]. Expert Systems with Applications, 2010, (37):6052-6060.
[6]	Wille R. Restructuring Lattice Theory: An Approach Based on Hierarchies of Concepts [M]. Rival I, ed. Ordered Sets. Dordrecht: Reidel, 1982: 445-470.
[7]	Formica A. Semantic Web search based on rough sets and Fuzzy Formal Concept Analysis [J]. Knowledge-Based Systems, 2012, (26):40-47.
[8]	Hu J H, Liu F X, Gu G D. Simitude degree and comparability direction of intuitionistic fuzzy singular rough sets [J]. International Conference on Computational and Information sciences, 2013, 53:2011-2014.
[9]	Su Y R, Xue C B. Explore the development and practical application of English teaching [J]. International Journal of Technology Management, 2014, (3):1-3.
[10]	Arinto P B. Issues and challenges in open and distance e-learning: perspectives from the Philippines [J]. Intemational Review of Research in Open and Distributed Learning, 2016, 17(2):23-27.
[11]	Microsoft. Microsoft Holo Lens [EB/OL]. https://www.microsoft.com/microsoft-hololens/en-u.s. 2017-02-10.
[12]	Zhao K, Chan C K K. Fostering collective and individual learning through knowledge building [J]. International Journal of Computer-supported Collaborative Learning, 2014, 9(1):63-95.
[13]	Makokha G L, Mutisya D N. Status of e-learning in public universities in Kenya [J]. International Review of Research in Open and Distributed Learning, 2016, 17(3):40-48.
[14]	Betty M R. Using a social networking tool for blended learning in staff training: sharing experience from practice [J]. Journal of Neonatal Nursing, 2014, 20:90-94.
[15]	Anaya A R, Luque M, Garcia-Saiz T. Recommender system in collaborative learning Environment an Influence Diagram [J]. Expert Systems with Applications, 2013, 40:7193-7202.
[16]	Simon R J M, Mucklow J. E-learning initiatives to support pre-scribing [J]. British Journal of Clinical Pharmacology, 2012, 74 (4):621-631.
[17]	Ana I, Molina M A. Redondo C L, et al. Assessing the effectiveness of new devices for accessing learning materials: An empirical analysis based on eye tracking and learner subjective perception [J]. Computers in Human Behavior, 2014, (31):475-490.
[18]	Soussan D, Marisa S, Tom T. Generation Y, web design and eye tracking [J]. International Journal of Human-Computer Studies, 2014, (5):307-323.

Cite This Article

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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

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

Download PDF

Sections

Plain Text BibTeX RIS

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

Copy | Download

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

Copy | Download

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

Copy | Download

@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