Extended Explicit Semantic Analysis for Calculating Semantic Relatedness of Web Resources
Key: SBD+10-1
Author: Philipp Scholl, Doreen Böhnstedt, Renato Domínguez García, Christoph Rensing, Ralf Steinmetz
Date: September 2010
Kind: In proceedings
Publisher: Springer Verlag
Book title: Sustaining TEL: From Innovation to Learning and Practice Proceedings of EC-TEL 2010
Keywords: Explicit Semantic Analysis, Semantic Relatedness, Wikipedia, Reference Corpus, Recommendation
Abstract: Finding semantically similar documents is a common task in Recommender Systems. Explicit Semantic Analysis (ESA) is an approach to calculate semantic relatedness between terms or documents based on similarities to documents of a reference corpus. Here, usually Wikipedia is applied as reference corpus. We propose enhancements to ESA (called Extended Explicit Semantic Analysis) that make use of further semantic properties of Wikipedia like article link structure and categorization, thus utilizing the additional semantic information that is included in Wikipedia. We show how we apply this approach to recommendation of web resource fragments in a resource-based learning scenario for self-directed, on-task learning with web resources.
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