RT Journal Article
T1 Cross-repository aggregation of educational resources
A1 Mouriño García, Marcos Antonio
A1 Pérez Rodríguez, Roberto
A1 Anido Rifón, Luis Eulogio
A1 Fernández Iglesias, Manuel José
A1 Darriba Bilbao, Víctor Manuel
K1 1203.04 Inteligencia Artificial
K1 1203.17 Informática
AB The proliferation of educational resource repositories promoted the development of aggregators to facilitate interoperability, that is, a unified access that would allow users to fetch a given resource independently of its origin. The CROERA system is a repository aggregator that provides access to educational resources independently of the classification taxonomy utilized in the hosting repository. For that, an automated classification algorithm is trained using the information extracted from the metadata of a collection of educational resources hosted in different repositories, which in turn depends on the classification taxonomy used in each case. Then, every resource will be automatically classified on demand independently of the original classification scheme. As a consequence, resources can be retrieved independently of the original taxonomy utilized using any taxonomy supported by the aggregator, and exploratory searches can be made without a previous taxonomy mapping. This approach overcomes one of the recurring problems in taxonomy mapping, namely the one-to-none matching situation. To evaluate the performance of this proposal two methods were applied. Resource classification in categories existing in all repositories was automatically evaluated, obtaining maximum performance values of 84% (F1 score), 87.8% (area under the receiver operator characteristic curve), 86% (area under the precision-recall curve) and 75.1% (Cohen's κ). In the case of resources not belonging to one of the common categories, human inspection was used as a reference to compute classification performance. In this case, maximum performance values obtained were respectively 69.8%, 73.8%, 75% and 54.3%. These results demonstrate the potential of this approach as a tool to facilitate resource classification, for example to provide a preliminary classification that would require just minor corrections from human classifiers.
PB Computers & Education
SN 03601315
YR 2018
FD 2018-02
LK http://hdl.handle.net/11093/5445
UL http://hdl.handle.net/11093/5445
LA eng
NO Computers & Education, 117, 31-49 (2018)
NO Xunta de Galicia | Ref. R2014/034 (RedPlir)
DS Investigo
RD 15-ene-2025