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

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Authors

Research Organisations

External Research Organisations

  • National Research Council Italy (CNR)
  • University of Amsterdam
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Details

Original languageEnglish
Title of host publicationProceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017
EditorsRonghuai Huang, Radu Vasiu, Kinshuk, Demetrios G Sampson, Nian-Shing Chen, Maiga Chang
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages522-524
Number of pages3
ISBN (electronic)9781538638705
Publication statusPublished - Aug 2017
Event17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017 - Timisoara, Romania
Duration: 3 Jul 20177 Jul 2017

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.

Keywords

    cross-language analysis, Digital methods, Search as learning

ASJC Scopus subject areas

Cite this

SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web. / Taibi, Davide; Fulantelli, Giovanni; Marenzi, Ivana et al.
Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017. ed. / Ronghuai Huang; Radu Vasiu; Kinshuk; Demetrios G Sampson; Nian-Shing Chen; Maiga Chang. Institute of Electrical and Electronics Engineers Inc., 2017. p. 522-524 8001849.

Research output: Chapter in book/report/conference proceedingConference contributionResearchpeer review

Taibi, D, Fulantelli, G, Marenzi, I, Nejdl, W, Rogers, R & Ijaz, A 2017, SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web. in R Huang, R Vasiu, Kinshuk, DG Sampson, N-S Chen & M Chang (eds), Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017., 8001849, Institute of Electrical and Electronics Engineers Inc., pp. 522-524, 17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017, Timisoara, Romania, 3 Jul 2017. https://doi.org/10.1109/icalt.2017.51
Taibi, D., Fulantelli, G., Marenzi, I., Nejdl, W., Rogers, R., & Ijaz, A. (2017). SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web. In R. Huang, R. Vasiu, Kinshuk, D. G. Sampson, N.-S. Chen, & M. Chang (Eds.), Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017 (pp. 522-524). Article 8001849 Institute of Electrical and Electronics Engineers Inc.. https://doi.org/10.1109/icalt.2017.51
Taibi D, Fulantelli G, Marenzi I, Nejdl W, Rogers R, Ijaz A. SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web. In Huang R, Vasiu R, Kinshuk, Sampson DG, Chen NS, Chang M, editors, Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017. Institute of Electrical and Electronics Engineers Inc. 2017. p. 522-524. 8001849 doi: 10.1109/icalt.2017.51
Taibi, Davide ; Fulantelli, Giovanni ; Marenzi, Ivana et al. / SaR-WEB : A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web. Proceedings - IEEE 17th International Conference on Advanced Learning Technologies, ICALT 2017. editor / Ronghuai Huang ; Radu Vasiu ; Kinshuk ; Demetrios G Sampson ; Nian-Shing Chen ; Maiga Chang. Institute of Electrical and Electronics Engineers Inc., 2017. pp. 522-524
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title = "SaR-WEB: A Semantic Web Tool to Support Search as Learning Practices and Cross-Language Results on the Web",
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.",
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author = "Davide Taibi and Giovanni Fulantelli and Ivana Marenzi and Wolfgang Nejdl and Richard Rogers and Asim Ijaz",
note = "Funding information: ACKNOWLEDGMENT This work was partially funded by the European commission in the context of the ALEXANDRIA project (ERC advanced grant no: 339233).; 17th IEEE International Conference on Advanced Learning Technologies, ICALT 2017 ; Conference date: 03-07-2017 Through 07-07-2017",
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AU - Fulantelli, Giovanni

AU - Marenzi, Ivana

AU - Nejdl, Wolfgang

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AB - 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.

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