SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web.

ICALT(2017)

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摘要
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 Bloomu0027s taxonomy such as: identifying and analyzing patterns, comparing, integrating, and creating new ideas.
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关键词
Digital methods, Search as learning, cross language analysis
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