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Reseach Article

Extracting IEEE LOM 9.4 using Memetic Algorithm for Textual Learning Objects

by Siddhartha Kumar Arjaria, Deepak Singh Tomar, Devshri Roy
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 85 - Number 8
Year of Publication: 2014
Authors: Siddhartha Kumar Arjaria, Deepak Singh Tomar, Devshri Roy
10.5120/14863-3237

Siddhartha Kumar Arjaria, Deepak Singh Tomar, Devshri Roy . Extracting IEEE LOM 9.4 using Memetic Algorithm for Textual Learning Objects. International Journal of Computer Applications. 85, 8 ( January 2014), 29-33. DOI=10.5120/14863-3237

@article{ 10.5120/14863-3237,
author = { Siddhartha Kumar Arjaria, Deepak Singh Tomar, Devshri Roy },
title = { Extracting IEEE LOM 9.4 using Memetic Algorithm for Textual Learning Objects },
journal = { International Journal of Computer Applications },
issue_date = { January 2014 },
volume = { 85 },
number = { 8 },
month = { January },
year = { 2014 },
issn = { 0975-8887 },
pages = { 29-33 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume85/number8/14863-3237/ },
doi = { 10.5120/14863-3237 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T22:01:57.674981+05:30
%A Siddhartha Kumar Arjaria
%A Deepak Singh Tomar
%A Devshri Roy
%T Extracting IEEE LOM 9.4 using Memetic Algorithm for Textual Learning Objects
%J International Journal of Computer Applications
%@ 0975-8887
%V 85
%N 8
%P 29-33
%D 2014
%I Foundation of Computer Science (FCS), NY, USA
Abstract

With the growing number of learning objects & their increasing use for learning, it is required to search the desired learning material in the least time. So it is needed to have the quality learning object. The quality of learning objects means they are tagged with correct & complete metadata. IEEE LOM set up a standard for uniformity of Meta data values. The IEEE LOM has 9 different categories for metadata. These categories are used to describe the learning object when filled with metadata values and in turn they are useful searching and understanding the learning object without actually opens it. IEEE LOM 9 category belongs to the classification and under this category, a important subcategory of IEEE LOM 9. 4 lies which actually belongs to keywords of learning objects. This paper uses the memetic algorithm based approach to extract the keywords for each learning objects of different classes. The correct keywords strongly reflect the learning object class and in turn it is very useful for user's point of view to decide whether this is the learning object he is searching for.

References
  1. IEEE. IEEE Std 1484. 12. 1-2002, IEEE Standard for Learning Object Metadata. http://www. ieee. org/.
  2. Greenberg, J. 2003. Metadata Generation: Processes, People and Tools. Bulletin of American Society for Information Science and Technology, 29(2) (Dec. 2003), 16-19.
  3. Steier, A. M. , and Belew, R. K. 1993. Exporting phrases: A statistical analysis of topical language. In R. Casey and B. Croft, editors, Second Symposium on Document Analysis and Information Retrieval, 179-190.
  4. Muñoz, A. 1996. Compound key word generation from document databases using a hierarchical clustering ART model. Intelligent Data Analysis. 1 (1)(1996),25-48.
  5. Yukio Ohsawa, Nels E. Benson, and Masahiko Yachida 1998. Keygraph: Automatic indexing by co-occurrence graph based on building construction metaphor. In Proceedings of the Advances in Digital Libraries Conference, ADL, IEEE Computer Society.
  6. Turney, P. 1999. Learning to extract key phrases from text. Technical report, National Research Council, Institute for Information Technology.
  7. Frank,E. , Paynther, G. W. , Witten, I. H. , Gutwin, C. & Nevil-Manning, C. G. 1999. Domain-specific key phrase extraction. In Proceedings of the 16th International Joint Conference on Artificial Intelligence.
  8. Y. Matsuo and M. Ishizuka 2004. Keyword extraction from a single document using word co-occurrence statistical information. International Journal on Artificial Intelligence Tools. 13(1) (2004), 157-169.
  9. G. Ercan and I. Cicekli 2007. Using lexical chains for keyword extraction. Information Processing & Management. 43(6)(2007), 1705–1714.
  10. Coursey, K. H. , Mihalcea R. , Moen,W. E. 2008. Automatic keyword extraction for learning object repositories. In Proceedings of the American Society for Information Science and Technology
  11. Dawkins, R 1976. The Selfish Gene. Clarendon Press, Oxford.
  12. Yew-Soon Ong, Meng-Hiot Lim, Ning Zhu, and Kok-Wai Wong 2006. Classification of Adaptive Memetic Algorithms:A Comparative Study. IEEE Transactions On Systems, Man, and Cybernetics—Part B: Cybernetics. 36(1)(February 2006), 141-152.
  13. F. Neri et al. (Eds. ) 2012. Handbook of Memetic Algorithms, Studies in Computational Intelligence, Springer. SCI 379, 43–52.
Index Terms

Computer Science
Information Sciences

Keywords

Learning Objects E-Learning Memetic Algorithm IEEE LOM.