Abstract
In this work, a new approach to automatic metadata extraction and semantic indexing for educational purposes is proposed to identify learning objects that may assist educators to prepare pedagogical materials from the Web. The model combines natural language processing techniques and machine learning methods to deal with semi-structured information on the web from which metadata are extracted. Experiments show the promise of the approach to effectively extract metadata web resources containing educational materials.
This research was partially supported by the National Council for Scientific and Technological Research (FONDECYT, Chile) under grant number 1130035: “An Evolutionary Computation Approach to Natural-Language Chunking for Biological Text Mining Applications”.
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Atkinson, J., Gonzalez, A., Munoz, M., Astudillo, H. (2013). Web Metadata Extraction and Semantic Indexing for Learning Objects Extraction. In: Ali, M., Bosse, T., Hindriks, K.V., Hoogendoorn, M., Jonker, C.M., Treur, J. (eds) Recent Trends in Applied Artificial Intelligence. IEA/AIE 2013. Lecture Notes in Computer Science(), vol 7906. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-38577-3_14
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DOI: https://doi.org/10.1007/978-3-642-38577-3_14
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