ASSESS: Automatic Self Assessment

The Linked Open Data Cloud is a goldmine for educational applications: First, it contains knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the meaning of the data can be understood by both humans and machines. 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 we can use Linked Data as 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. Teachers are supported through the automatic generation and evaluation of tests. Our evaluation shows that ASSESS scales on very large knowledge bases such as DBpedia.

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The Linked Open Data Cloud is a goldmine for educational applications: First, it contains knowledge of encyclopedic nature on a large number of real-world entities. Moreover, the data being structured ensures that the meaning of the data can be understood by both humans and machines. 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 we can use Linked Data as 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. Teachers are supported through the automatic generation and evaluation of tests. Our evaluation shows that ASSESS scales on very large knowledge bases such as DBpedia.

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News

DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released ( 2019-09-24T22:41:46+02:00 by Simon Bin)

2019-09-24T22:41:46+02:00 by Simon Bin

Dear all, The Smart Data Analytics group [1] and the E.T.-db-MOLE sub-group located at the InfAI Leipzig [2] is happy to announce DL-Learner 1.4. DL-Learner is a framework containing algorithms for supervised machine learning in RDF and OWL. Read more about "DL-Learner 1.4 (Supervised Structured Machine Learning Framework) Released"

DBpedia Day @ SEMANTiCS 2019 ( 2019-08-01T10:35:05+02:00 by Sandra Bartsch)

2019-08-01T10:35:05+02:00 by Sandra Bartsch

 We are happy to announce that SEMANTiCS 2019 will host the 14th DBpedia Community Meeting at the last day of the conference on September 12, 2019. Read more about "DBpedia Day @ SEMANTiCS 2019"

LDK conference @ University of Leipzig ( 2019-03-22T09:21:41+01:00 by Julia Holze)

2019-03-22T09:21:41+01:00 by Julia Holze

With the advent of digital technologies, an ever-increasing amount of language data is now available across various application areas and industry sectors, thus making language data more and more valuable. Read more about "LDK conference @ University of Leipzig"

13th DBpedia community meeting in Leipzig ( 2019-02-22T12:22:07+01:00 by Julia Holze)

2019-02-22T12:22:07+01:00 by Julia Holze

We are happy to invite you to join the 13th edition of the DBpedia Community Meeting, which will be held in Leipzig. Read more about "13th DBpedia community meeting in Leipzig"

SANSA 0.5 (Semantic Analytics Stack) Released ( 2018-12-13T09:25:34+01:00 by Prof. Dr. Jens Lehmann)

2018-12-13T09:25:34+01:00 by Prof. Dr. Jens Lehmann

We are happy to announce SANSA 0.5 – the fifth release of the Scalable Semantic Analytics Stack. Read more about "SANSA 0.5 (Semantic Analytics Stack) Released"