On the design of learning objects classifiers. In pages 464-468, 2010. doi abstract bibtex An important limitation of learning object repositories is that they frequently provide incomplete or imperfect information to describe the resources that they index. A form of dealing with this limitation is to categorize the learning objects in a taxonomy that allows main themes to be identified that cover each of these resources. In this paper, we will explore two techniques to categorize learning objects: language models and logistic regression models. Experiments show that the logistic regression method obtains results with high precision. © 2010 IEEE.
@inproceedings{10.1109/ICALT.2010.135,
abstract = "An important limitation of learning object repositories is that they frequently provide incomplete or imperfect information to describe the resources that they index. A form of dealing with this limitation is to categorize the learning objects in a taxonomy that allows main themes to be identified that cover each of these resources. In this paper, we will explore two techniques to categorize learning objects: language models and logistic regression models. Experiments show that the logistic regression method obtains results with high precision. © 2010 IEEE.",
year = "2010",
title = "On the design of learning objects classifiers",
pages = "464-468",
doi = "10.1109/ICALT.2010.135",
journal = "Proceedings - 10th IEEE International Conference on Advanced Learning Technologies, ICALT 2010"
}
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