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 2021 ( 2021-07-30T09:54:45+02:00 by Julia Holze)

2021-07-30T09:54:45+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 9, 2021. Read more about "DBpedia Day @ SEMANTiCS 2021"

LDK Conference meets DBpedia in Zaragoza, Spain ( 2021-07-09T10:37:27+02:00 by Julia Holze)

2021-07-09T10:37:27+02:00 by Julia Holze

We are happy to announce that we will organize a DBpedia Tutorial on September 1, 2021 in Zaragoza, Spain. This DBpedia tutorial will be part of the Language, Data and Knowledge conference 2021. Read more about "LDK Conference meets DBpedia in Zaragoza, Spain"

Assessing Language Identification Over DBpedia ( 2021-05-04T23:27:40+02:00 EdgardMarx)

2021-05-04T23:27:40+02:00 EdgardMarx

Large-scale multilingual knowledge bases (KBs) are the key for cross-lingual and multilingual applications such as Question Answering, Machine  Translation,  and  Search. Read more about "Assessing Language Identification Over DBpedia"

DBpedia Tutorial @ Knowledge Graph Conference 2021 ( 2021-04-09T13:20:50+02:00 by Julia Holze)

2021-04-09T13:20:50+02:00 by Julia Holze

On May 4, 2021 we will organize a tutorial at the Knowledge Graph Conference (KGC) 2021. Read more about "DBpedia Tutorial @ Knowledge Graph Conference 2021"

DBpedia @ Google Summer of Code program 2021 ( 2021-03-15T09:41:22+01:00 by Julia Holze)

2021-03-15T09:41:22+01:00 by Julia Holze

DBpedia, one of InfAI’s community projects, will participate in the Google Summer of Code (GSoC) program for the 10th time. 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 2021"