Automatic topic terms identification from OER
Author:
Affiliation:
1. Dept. Computer Science and Electronics, Technical University of Loja, Ecuador
2. Dept. Computer Science and Electronics, Technical University of Loja, Ecuador and Polytechnic University of Madrid, Spain
Publisher
ACM
Link
https://dl.acm.org/doi/pdf/10.1145/3629296.3629346
Reference18 articles.
1. Probabilistic topic models
2. David M Blei , Andrew Y Ng , and Michael Jordan . 2003 . Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, (2003), 993–1022 . Retrieved March 25, 2019 from http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf David M Blei, Andrew Y Ng, and Michael Jordan. 2003. Latent Dirichlet Allocation. J. Mach. Learn. Res. 3, (2003), 993–1022. Retrieved March 25, 2019 from http://www.jmlr.org/papers/volume3/blei03a/blei03a.pdf
3. Finding out topics in educational materials using their components
4. Accurate and effective latent concept modeling for ad hoc information retrieval
5. Application of the LDA Model to Semantic Annotation of Web-based English Educational Resources
1.学者识别学者识别
2.学术分析学术分析
3.人才评估人才评估
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