ASSESS — automatic self-assessment using linked data

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Standard

ASSESS — automatic self-assessment using linked data. / Bühmann, Lorenz; Usbeck, Ricardo; Ngonga Ngomo, Axel Cyrille.
The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings. ed. / Marcelo Arenas; Oscar Corcho; Elena Simperl; Markus Strohmaier; Mathieu d’Aquin; Kavitha Srinivas; Paul Groth; Michel Dumontier; Jeff Heflin; Krishnaprasad Thirunarayan; Steffen Staab. Springer-Verlag Wien, 2015. p. 76-89 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9367).

Research output: Contributions to collected editions/worksArticle in conference proceedingsResearchpeer-review

Harvard

Bühmann, L, Usbeck, R & Ngonga Ngomo, AC 2015, ASSESS — automatic self-assessment using linked data. in M Arenas, O Corcho, E Simperl, M Strohmaier, M d’Aquin, K Srinivas, P Groth, M Dumontier, J Heflin, K Thirunarayan & S Staab (eds), The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9367, Springer-Verlag Wien, pp. 76-89, 14th International Semantic Web Conference, ISWC 2015, Bethlehem, Pennsylvania, United States, 11.10.15. https://doi.org/10.1007/978-3-319-25010-6_5

APA

Bühmann, L., Usbeck, R., & Ngonga Ngomo, A. C. (2015). ASSESS — automatic self-assessment using linked data. In M. Arenas, O. Corcho, E. Simperl, M. Strohmaier, M. d’Aquin, K. Srinivas, P. Groth, M. Dumontier, J. Heflin, K. Thirunarayan, & S. Staab (Eds.), The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings (pp. 76-89). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9367). Springer-Verlag Wien. https://doi.org/10.1007/978-3-319-25010-6_5

Vancouver

Bühmann L, Usbeck R, Ngonga Ngomo AC. ASSESS — automatic self-assessment using linked data. In Arenas M, Corcho O, Simperl E, Strohmaier M, d’Aquin M, Srinivas K, Groth P, Dumontier M, Heflin J, Thirunarayan K, Staab S, editors, The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings. Springer-Verlag Wien. 2015. p. 76-89. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-25010-6_5

Bibtex

@inbook{95be9553e3744b618f40e205d302a519,
title = "ASSESS — automatic self-assessment using linked data",
abstract = "The Linked Open Data Cloud is a goldmine for creating open and low-cost educational applications: First, it contains open knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the data is both human and machine-readable. Finally, the openness of the data and the use of RDF as standard format facilitate the development of applications that can be ported across different domains with ease. However, RDF is still unknown to most members of the target audience of educational applications. Thus, Linked Data has commonly been used for the description or annotation of educational data. Yet, Linked Data has (to the best of our knowledge) never been used as direct source of educational material. With ASSESS, we demonstrate that Linked Data can be used as a source for the automatic generation of educational material. By using innovative RDF verbalization and entity summarization technology, we bridge between natural language and RDF. We then use RDF data directly to generate quizzes which encompass questions of different types on user defined domains of interest. By these means, we enable learners to generate self-assessment tests on domains of interest. Our evaluation shows that ASSESS generates high-quality English questions. Moreover, our usability evaluation suggests that our interface can be used intuitively. Finally, our test on DBpedia shows that our approach can be deployed on very large knowledge bases.",
keywords = "Informatics, inferior vena cava, educational material, link data, automatic generation, data layer, Business informatics",
author = "Lorenz B{\"u}hmann and Ricardo Usbeck and {Ngonga Ngomo}, {Axel Cyrille}",
note = "Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 14th International Semantic Web Conference, ISWC 2015, ISWC 2015 ; Conference date: 11-10-2015 Through 15-10-2015",
year = "2015",
doi = "10.1007/978-3-319-25010-6_5",
language = "English",
isbn = "978-3-319-25009-0",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer-Verlag Wien",
pages = "76--89",
editor = "Marcelo Arenas and Oscar Corcho and Elena Simperl and Markus Strohmaier and Mathieu d{\textquoteright}Aquin and Kavitha Srinivas and Paul Groth and Michel Dumontier and Jeff Heflin and Krishnaprasad Thirunarayan and Steffen Staab",
booktitle = "The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings",
address = "Austria",
url = "http://iswc2015.semanticweb.org/",

}

RIS

TY - CHAP

T1 - ASSESS — automatic self-assessment using linked data

AU - Bühmann, Lorenz

AU - Usbeck, Ricardo

AU - Ngonga Ngomo, Axel Cyrille

N1 - Publisher Copyright: © Springer International Publishing Switzerland 2015.

PY - 2015

Y1 - 2015

N2 - The Linked Open Data Cloud is a goldmine for creating open and low-cost educational applications: First, it contains open knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the data is both human and machine-readable. Finally, the openness of the data and the use of RDF as standard format facilitate the development of applications that can be ported across different domains with ease. However, RDF is still unknown to most members of the target audience of educational applications. Thus, Linked Data has commonly been used for the description or annotation of educational data. Yet, Linked Data has (to the best of our knowledge) never been used as direct source of educational material. With ASSESS, we demonstrate that Linked Data can be used as a source for the automatic generation of educational material. By using innovative RDF verbalization and entity summarization technology, we bridge between natural language and RDF. We then use RDF data directly to generate quizzes which encompass questions of different types on user defined domains of interest. By these means, we enable learners to generate self-assessment tests on domains of interest. Our evaluation shows that ASSESS generates high-quality English questions. Moreover, our usability evaluation suggests that our interface can be used intuitively. Finally, our test on DBpedia shows that our approach can be deployed on very large knowledge bases.

AB - The Linked Open Data Cloud is a goldmine for creating open and low-cost educational applications: First, it contains open knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the data is both human and machine-readable. Finally, the openness of the data and the use of RDF as standard format facilitate the development of applications that can be ported across different domains with ease. However, RDF is still unknown to most members of the target audience of educational applications. Thus, Linked Data has commonly been used for the description or annotation of educational data. Yet, Linked Data has (to the best of our knowledge) never been used as direct source of educational material. With ASSESS, we demonstrate that Linked Data can be used as a source for the automatic generation of educational material. By using innovative RDF verbalization and entity summarization technology, we bridge between natural language and RDF. We then use RDF data directly to generate quizzes which encompass questions of different types on user defined domains of interest. By these means, we enable learners to generate self-assessment tests on domains of interest. Our evaluation shows that ASSESS generates high-quality English questions. Moreover, our usability evaluation suggests that our interface can be used intuitively. Finally, our test on DBpedia shows that our approach can be deployed on very large knowledge bases.

KW - Informatics

KW - inferior vena cava

KW - educational material

KW - link data

KW - automatic generation

KW - data layer

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84952646935&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/60436f24-e810-3fde-add7-8eeaebdfb5a1/

U2 - 10.1007/978-3-319-25010-6_5

DO - 10.1007/978-3-319-25010-6_5

M3 - Article in conference proceedings

AN - SCOPUS:84952646935

SN - 978-3-319-25009-0

T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

SP - 76

EP - 89

BT - The Semantic Web – ISWC 2015 - 14th International Semantic Web Conference, Proceedings

A2 - Arenas, Marcelo

A2 - Corcho, Oscar

A2 - Simperl, Elena

A2 - Strohmaier, Markus

A2 - d’Aquin, Mathieu

A2 - Srinivas, Kavitha

A2 - Groth, Paul

A2 - Dumontier, Michel

A2 - Heflin, Jeff

A2 - Thirunarayan, Krishnaprasad

A2 - Staab, Steffen

PB - Springer-Verlag Wien

T2 - 14th International Semantic Web Conference, ISWC 2015

Y2 - 11 October 2015 through 15 October 2015

ER -