A Survey: Framework to Develop Retrieval Algorithms of Indexing Techniques on Learning Material
Keywords:
Indexing Technique, Data Mining, Retrieval Algorithms, Learning Material, Text, Graphic, Video, Framework,Abstract
This paper presents a review on indexing techniques to develop retrieval algorithms framework on learning material. Analysis of the framework was drawn from surveys on literature review and experiment on online campus Learning Materials. Data indexing problem of online learning material occurs as online data comprising many types, formats and words of documents on the system become larger daily. Thus, searching capability for relevant information becomes slower. Further, it becomes more difficult to get the correct information as the learning materials consists of multiple forms of documents such as words, images and videos. The objective of this research is to analyze the existing indexing technique in modeling new retrieval indexing algorithms framework mainly for data mining. Four existing indexing techniques for learning material were reviewed. It is identified that the best used technique are Inverted File, Suffix Array, Suffix Tree and Signature File. Based on the four techniques, characterizations and parameters to enhance a new indexing technique (NIT) was identified and five User Acceptance Tests (UAT) were performed. A framework for NIT was designed and experiments are done on a Campus Learning Material. Identified parameters were successfully inserted in the five test experiments. The conceptual framework was continuously applied to develop NIT for retrieval algorithms on learning material. This research is significant for fast accessing on real life campus learning material system that benefits users and fast retrieval of needed information.References
Day, R.E., An Afterword to Indexing It All: The Subject in the Age of Documentation, Information, and Data. Bulletin of the Association for Information Science and Technology, (2016), Vol 42(2): p. 25-28.
Darvishi, A. and H. Hassanpour, A Geometric View of Similarity Measures in Data Mining. International Journal of EngineeringTransactions C: Aspects, (2015), Vol 28(12): p. 1728.
Hashemzadeh, E., Hamidi, H., Using a Data Mining Tool and FPgrowth Algorithm Application for Extraction of the Rules in Two Different Dataset, International Journal of Engineering (IJE) Transactions C: Aspects, (2016) Vol. 29, No. 6.
Golub, K., et al., A framework for evaluating automatic indexing or classification in the context of retrieval. Journal of the Association for Information Science and Technology, (2016), Vol 67(1), p. 3-16.
Yadav, A.K., D. Yadav, and D. Rai, Efficient Methods to Generate Inverted Indexes for IR, in Information Systems Design and Intelligent Applications, Springer. (2016), p. 431-440.
Bilimoria, D.M., P.A. Patel, and M.S. Rajpoot, Supporting Linked Databases in Keyword Query Searching Using Density Inverted Indexes, Emerging Research in Computing, Information, Communication and Applications, Springer. (2016), p. 367-375.
Constantin, C., et al., AS-Index: A Structure For String Search Using n-grams and Algebraic Signatures. Journal of Computer Science and Technology, (2016), Vol 31(1): p. 147-166.
Ganguly, A., Shah, R., Thankachan, S.V., Parameterized Pattern Matching--Succinctly. Cornell University Library, arXiv preprint arXiv, (2016), 1603.07457.
Ponvert, E., W. Kalter, and J. Szalay, Suffix searching on documents, Google Patents. (2016).
Singh, M.P., Dhaka, V., Handwritten character recognition using modified gradient descent technique of neural networks and representation of conjugate descent for training patterns. Database Journal, (2008), Vol 5, p. 20.
B'ez, Y.A. and R.C.C. Jiménez. Indexing structured documents with suffix arrays. 2012 12th IEEE International Conference on Computational Science and Its Applications (ICCSA), (2012).
Zhu, C., Zhu, C., Li, Q., Kong, L., Wang, X., Hong, X., Associated Index for Big Structured and Unstructured Data, Springer Web-Age Information Management, (2015), p. 567-570.
Kras ̌ na, M., M. Duh, and T. Bratina. E-learning next step Learning materials for students, 2014 37th IEEE International Convention Information and Communication Technology, Electronics and Microelectronics (MIPRO), (2014).
Abdullah, M.F. and K. Ahmad. Business intelligence model for unstructured data management. 2015 IEEE International Conference on Electrical Engineering and Informatics (ICEEI), (2015).
Ferguson, R. and S.B. Shum, Towards a social learning space for open educational resources. Collaborative LearningBook, The Open University (2012), Vol 2: p. 309-327.
Sampson, D.G., Zervas, P., Sotiriou, S., Agogi, E., Sharing of open science education resources and educational practices in Europe. Open Educational Resources: Innovation, Research and Practice,(2013), p. 105.
Sicilia, M.A., Garcia, E., On the concepts of usability and reusability of learning objects. The International Review of Research in Open and Distributed Learning, (2003), Vol 4(2).
Sharma, M., Patel, R., A Survey on Information Retrieval Models, Techniques And Applications. International Journal of Emerging Technology and Advanced Engineering, (2013), p. 2250-2459.
Arbain, A.S., M. Kassim, Saaidin, S., Systematic Test and Evaluation Process (STEP) approach on Shared Banking Services (SBS) System identification. 2010 2nd International Conference on Education Technology and Computer. (2010).
Smeaton, A.F., Techniques used and open challenges to the analysis, indexing and retrieval of digital video. Information Systems, (2007), 32(4): p. 545-559.
Downloads
Published
How to Cite
Issue
Section
License
TRANSFER OF COPYRIGHT AGREEMENT
The manuscript is herewith submitted for publication in the Journal of Telecommunication, Electronic and Computer Engineering (JTEC). It has not been published before, and it is not under consideration for publication in any other journals. It contains no material that is scandalous, obscene, libelous or otherwise contrary to law. When the manuscript is accepted for publication, I, as the author, hereby agree to transfer to JTEC, all rights including those pertaining to electronic forms and transmissions, under existing copyright laws, except for the following, which the author(s) specifically retain(s):
- All proprietary right other than copyright, such as patent rights
- The right to make further copies of all or part of the published article for my use in classroom teaching
- The right to reuse all or part of this manuscript in a compilation of my own works or in a textbook of which I am the author; and
- The right to make copies of the published work for internal distribution within the institution that employs me
I agree that copies made under these circumstances will continue to carry the copyright notice that appears in the original published work. I agree to inform my co-authors, if any, of the above terms. I certify that I have obtained written permission for the use of text, tables, and/or illustrations from any copyrighted source(s), and I agree to supply such written permission(s) to JTEC upon request.