Investigating eLearning Research Trends in Iran via Automatic Semantic Network Generation
| Autor: | Maedeh Mosharraf, Fattaneh Taghiyareh, Sara Alaee |
|---|---|
| Rok vydání: | 2017 |
| Předmět: |
Information Systems and Management
Information retrieval Computer science 02 engineering and technology Pointwise mutual information Semantic network World Wide Web Knowledge extraction 020204 information systems 0202 electrical engineering electronic engineering information engineering 020201 artificial intelligence & image processing Enhanced Data Rates for GSM Evolution Cluster analysis Information Systems |
| Zdroj: | Journal of Global Information Technology Management. 20:91-109 |
| ISSN: | 2333-6846 1097-198X |
| DOI: | 10.1080/1097198x.2017.1321355 |
| Popis: | The purpose of this study is to investigate Iran’s eLearning research status in comparison with the world. We propose a method based on a text mining approach for extracting knowledge from Iranian published articles and generating the corresponding semantic network automatically. eLearning concepts are extracted from papers published in 6 years’ proceedings of ICeLeT, an International Conference on eLearning and eTeaching, in Iran. After extracting the domain-specific concepts, each pair of concepts get the possibility to be linked together based on co-occurrence in the articles. A weight is assigned to each edge according to the pointwise mutual information value of the pair of concepts. To identify gaps between the latest local and global research, the obtained semantic network is compared with another semantic network extracted from 6 years’ proceedings of ICALT, an International Conference on Advanced Learning Technologies. By applying a hybrid clustering algorithm on two networks based on the... |
| Databáze: | OpenAIRE |
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