Identifying Semantic Classes within Student’s Data Using Clustering Technique

Marek Jaszuk, Teresa Mroczek, Barbara Fryc

2014

Abstract

The paper discusses the problem of discovering semantic classes which are the basic building block of any semantic model. A methods based on clustering techniques is proposed, which leads to discovering related data coming from survey questions and other sources of information. We explain how the questions can be interpreted as belonging to the same semantic class. Discovering semantic classes is assumed to be foundation for construction of the knowledge model (ontology) describing objects being the subjects of the survey. The ultimate goal of the research is developing a methodology for automatic building of semantic models from the data. In our case the surveys refer to different socio-economic factors describing student’s situation. Thus the particular goal of the work is construction of the knowledge model, which would allow for predicting the possible outcomes of the educational process. The research is, however, more general, and its results could be used for analyzing collections of objects, for which we have data coming from surveys, and possibly some additional sources of information.

References

  1. A. Gmez-Prez, M. Fernndez-Lpez, O. C. (2007). Ontological Engineering: with examples from the areas of Knowledge Management, e-Commerce and the Semantic Web. (Advanced Information and Knowledge Processing). Springer-Verlag, New York.
  2. G. S. Davidson, e. a. (2010). Data Mining for Ontology Development. Sandia National Laboratories, Albuquerque.
  3. Gorskis, H. and Chizhof, Y. (2012). Ontology building using data mining techniques. Information Technology and Management Science, 15:183-188.
  4. N. F. Noy, D. L. M. (2001). Ontology Development 101: A Guide to Creating Your First Ontology. Stanford University, Stanford.
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Paper Citation


in Harvard Style

Jaszuk M., Mroczek T. and Fryc B. (2014). Identifying Semantic Classes within Student’s Data Using Clustering Technique . In Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA, ISBN 978-989-758-035-2, pages 371-376. DOI: 10.5220/0005111403710376


in Bibtex Style

@conference{data14,
author={Marek Jaszuk and Teresa Mroczek and Barbara Fryc},
title={Identifying Semantic Classes within Student’s Data Using Clustering Technique},
booktitle={Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,},
year={2014},
pages={371-376},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0005111403710376},
isbn={978-989-758-035-2},
}


in EndNote Style

TY - CONF
JO - Proceedings of 3rd International Conference on Data Management Technologies and Applications - Volume 1: DATA,
TI - Identifying Semantic Classes within Student’s Data Using Clustering Technique
SN - 978-989-758-035-2
AU - Jaszuk M.
AU - Mroczek T.
AU - Fryc B.
PY - 2014
SP - 371
EP - 376
DO - 10.5220/0005111403710376