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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Bahrami, A. |
| Copyright Year | 2010 |
| Abstract | An e-lesson can be of Homogeneous or Semi-homogeneous nature. Even if a subset of such e-lessons has only one module (m1) in common with other subsets, the “common module” may not contain the same array of concepts. As a result, any investigation of such e-lessons based solely on their module names is inherently flawed. Normalization of e-lessons can remove such a flaw. A set of N Homogeneous and Semi-homogenous e-lessons are considered normalized if same-name modules cover the same concepts. In this paper a framework for normalization of e-lessons is presented as the first phase of creating a mechanism for accurate e-lesson modules’ cross-referencing, indexing, retrieving, and data mining. |
| Starting Page | 1063 |
| Ending Page | 1068 |
| File Size | 1072626 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424462704 |
| e-ISBN | 9781424462711 |
| DOI | 10.1109/ITNG.2010.56 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-04-12 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | E-lesson Normalization Electronic learning Theory of automata Learning automata Doped fiber amplifiers Information retrieval Data mining Information technology Homogeneous e-lessons Module Normalization Indexing Semi-homogenous e-lessons |
| Content Type | Text |
| Resource Type | Article |
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