SaR-WEB: A Semantic Web tool to support Search as Learning practices and cross-language results on the web

Authors
  • D. Taibi
  • G. Fulantelli
  • I. Marenzi
  • W. Nejdl
Publication date 2017
Host editors
  • M. Chang
  • N.-S. Chen
  • R. Huang
  • Kinshuk
  • D.G. Sampson
  • R. Vasiu
Book title ICALT 2017 : IEEE 17th International Conference on Advanced Learning Technologies
Book subtitle proceedings : 3-7 July 2017, Timisoara, Romania
ISBN
  • 9781538638705
Event IEEE 17th International Conference on Advanced Learning Technologies
Pages (from-to) 522-524
Publisher Los Alamitos, California: IEEE Computer Society
Organisations
  • Faculty of Humanities (FGw) - Amsterdam Institute for Humanities Research (AIHR) - Amsterdam School for Cultural Analysis (ASCA)
Abstract
In this paper, we present SaR-Web, a multimodal web search tool that provides automatic support to searching as learning processes. Inspired by the work of Richard Rogers and the Digital Methods Initiative, SaR-Web compares the results of queries across search engine language domains, and visualizes search results with a semantic added value, thus facilitating cross-linguistic and cross-cultural comparisons of results. The comparison between search results in different languages is enabled through the visualization of semantic concepts extracted by means of a NER tool from the search results. The SaR-Web system has the potential to support highlevel learning activities described in Bloom's taxonomy such as: identifying and analyzing patterns, comparing, integrating, and creating new ideas.
Document type Conference contribution
Language English
Published at https://doi.org/10.1109/ICALT.2017.51
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