Cross-Language Semantic Relatedness
| Cross-Language Semantic Relatedness|
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Cross-Language Semantic Relatedness is included as keyword or extra keyword in 0 datasets, 0 tools and 1 publications.
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|Title||Author(s)||Published in||Language||DateThis property is a special property in this wiki.||Abstract||R||C|
|Cross-lingual recommendations in a resource-based learning scenario||Schmidt S.
|Lecture Notes in Computer Science||English||2011||CROKODIL is a platform supporting resource-based learning scenarios for self-directed, on-task learning with web resources. As CROKODIL enables the forming of possibly large learning communities, the stored data is growing in a large scale. Thus, an appropriate recommendation of tags and learning resources becomes increasingly important for supporting learners. We propose semantic relatedness between tags and resources as a basis of recommendation and identify Explicit Semantic Analysis (ESA) using Wikipedia as reference corpus as a viable option. However, data from CROKODIL shows that tags and resources are often composed in different languages. Thus, a monolingual approach to provide recommendations is not applicable in CROKODIL. Thus, we examine strategies for providing mappings between different languages, extending ESA to provide cross-lingual capabilities. Specifically, we present mapping strategies that utilize additional semantic information contained in Wikipedia. Based on CROKODIL's application scenario, we present an evaluation design and show results of cross-lingual ESA.||0||0|