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

DBpedia Day @ SEMANTiCS 2022 ( 2022-08-08T11:24:02+02:00 by Julia Holze)

2022-08-08T11:24:02+02:00 by Julia Holze

We are happy to announce that we are partnering again with the SEMANTiCS Conference which will host this year’s DBpedia Day on September 13, 2022. Read more about "DBpedia Day @ SEMANTiCS 2022"

DBpedia Knowledge Engineering PhD Symposium ( 2022-05-02T16:59:37+02:00 by Julia Holze)

2022-05-02T16:59:37+02:00 by Julia Holze

Dear all,  We are excited to invite you to the 1st DBpedia Knowledge Engineering PhD Symposium, organized on July 6th, 2022 in Leipzig, Germany. Read more about "DBpedia Knowledge Engineering PhD Symposium"

Tutorial @ Knowledge Graph Conference 2022 ( 2022-04-25T12:24:06+02:00 by Julia Holze)

2022-04-25T12:24:06+02:00 by Julia Holze

On May 2, 2022 we will organize a tutorial 2.0 at the Knowledge Graph Conference (KGC) 2022. Read more about "Tutorial @ Knowledge Graph Conference 2022"

International Workshop on Data-driven Resilience Research 2022 ( 2022-04-21T14:43:27+02:00 by Julia Holze)

2022-04-21T14:43:27+02:00 by Julia Holze

In the face of continuously changing contextual conditions and ubiquitous disruptive crisis events, the concept of resilience refers to some of the most urgent, challenging, and interesting issues of nowadays society. Read more about "International Workshop on Data-driven Resilience Research 2022"

DBpedia @ Google Summer of Code Program 2022 ( 2022-03-23T14:26:48+01:00 by Julia Holze)

2022-03-23T14:26:48+01:00 by Julia Holze

DBpedia, one of InfAI’s community projects, will be part of the 11th Google Summer of Code (GSoC) program. The GSoC program has the goal to bring students from all over the globe into open source software development. Read more about "DBpedia @ Google Summer of Code Program 2022"