CubeQA—question answering on RDF data cubes
Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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CubeQA—question answering on RDF data cubes. / Höffner, Konrad; Lehmann, Jens; Usbeck, Ricardo.
The Semantic Web – ISWC 2016: 15th International Semantic Web Conference, Kobe, Japan, October 17–21, 2016, Proceedings, Part I. Hrsg. / Paul Groth; Elena Simperl; Alasdair Gray; Marta Sabou; Markus Krotzsch; Freddy Lecue; Freddy Lecue; Fabian Flock; Yolanda Gil. Springer-Verlag Wien, 2016. S. 325-340 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Band 9981 LNCS).Publikation: Beiträge in Sammelwerken › Aufsätze in Konferenzbänden › Forschung › begutachtet
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TY - CHAP
T1 - CubeQA—question answering on RDF data cubes
AU - Höffner, Konrad
AU - Lehmann, Jens
AU - Usbeck, Ricardo
N1 - Conference code: 15
PY - 2016/1/1
Y1 - 2016/1/1
N2 - Statistical data in the form of RDF Data Cubes is becoming increasingly valuable as it influences decisions in areas such as health care, policy and finance. While a growing amount is becoming freely available through the open data movement, this data is opaque to laypersons. Semantic Question Answering (SQA) technologies provide intuitive access via free-form natural language queries but general SQA systems cannot process RDF Data Cubes. On the intersection between RDF Data Cubes and SQA, we create a new subfield of SQA, called RDCQA. We create an RDQCA benchmark as task 3 of the QALD-6 evaluation challenge, to stimulate further research and enable quantitative comparison between RDCQA systems. We design and evaluate the domain independent CubeQA algorithm, which is the first RDCQA system and achieves a global F1 score of 0.43 on the QALD6T3-test benchmark, showing that RDCQA is feasible.
AB - Statistical data in the form of RDF Data Cubes is becoming increasingly valuable as it influences decisions in areas such as health care, policy and finance. While a growing amount is becoming freely available through the open data movement, this data is opaque to laypersons. Semantic Question Answering (SQA) technologies provide intuitive access via free-form natural language queries but general SQA systems cannot process RDF Data Cubes. On the intersection between RDF Data Cubes and SQA, we create a new subfield of SQA, called RDCQA. We create an RDQCA benchmark as task 3 of the QALD-6 evaluation challenge, to stimulate further research and enable quantitative comparison between RDCQA systems. We design and evaluate the domain independent CubeQA algorithm, which is the first RDCQA system and achieves a global F1 score of 0.43 on the QALD6T3-test benchmark, showing that RDCQA is feasible.
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=84992533287&partnerID=8YFLogxK
UR - https://www.mendeley.com/catalogue/146cc2e7-011a-3a75-86d1-1adf6a78c437/
U2 - 10.1007/978-3-319-46523-4_20
DO - 10.1007/978-3-319-46523-4_20
M3 - Article in conference proceedings
AN - SCOPUS:84992533287
SN - 978-3-319-46522-7
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 325
EP - 340
BT - The Semantic Web – ISWC 2016
A2 - Groth, Paul
A2 - Simperl, Elena
A2 - Gray, Alasdair
A2 - Sabou, Marta
A2 - Krotzsch, Markus
A2 - Lecue, Freddy
A2 - Lecue, Freddy
A2 - Flock, Fabian
A2 - Gil, Yolanda
PB - Springer-Verlag Wien
T2 - 15th International Semantic Web Conference, ISWC 2016
Y2 - 17 October 2016 through 21 October 2016
ER -