HAWK - hybrid question answering using linked data

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

Standard

HAWK - hybrid question answering using linked data. / Usbeck, Ricardo; Ngomo, Axel Cyrille Ngonga; Bühmann, Lorenz et al.
The Semantic Web: Latest Advances and New Domains - 12th European Semantic Web Conference, ESWC 2015, Proceedings. ed. / Fabien Gandon; Harald Sack; Antoine Zimmermann; Marta Sabou; Claudia d’Amato; Philippe Cudré-Mauroux. Springer Nature Switzerland AG, 2015. p. 353-368 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9088).

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

Harvard

Usbeck, R, Ngomo, ACN, Bühmann, L & Unger, C 2015, HAWK - hybrid question answering using linked data. in F Gandon, H Sack, A Zimmermann, M Sabou, C d’Amato & P Cudré-Mauroux (eds), The Semantic Web: Latest Advances and New Domains - 12th European Semantic Web Conference, ESWC 2015, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 9088, Springer Nature Switzerland AG, pp. 353-368, 12th European Semantic Web Conference - ESWC 2015, Portoroz, Slovenia, 31.05.15. https://doi.org/10.1007/978-3-319-18818-8_22

APA

Usbeck, R., Ngomo, A. C. N., Bühmann, L., & Unger, C. (2015). HAWK - hybrid question answering using linked data. In F. Gandon, H. Sack, A. Zimmermann, M. Sabou, C. d’Amato, & P. Cudré-Mauroux (Eds.), The Semantic Web: Latest Advances and New Domains - 12th European Semantic Web Conference, ESWC 2015, Proceedings (pp. 353-368). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 9088). Springer Nature Switzerland AG. https://doi.org/10.1007/978-3-319-18818-8_22

Vancouver

Usbeck R, Ngomo ACN, Bühmann L, Unger C. HAWK - hybrid question answering using linked data. In Gandon F, Sack H, Zimmermann A, Sabou M, d’Amato C, Cudré-Mauroux P, editors, The Semantic Web: Latest Advances and New Domains - 12th European Semantic Web Conference, ESWC 2015, Proceedings. Springer Nature Switzerland AG. 2015. p. 353-368. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-319-18818-8_22

Bibtex

@inbook{e88eccf4361848f1a89353b85d1a93e6,
title = "HAWK - hybrid question answering using linked data",
abstract = "The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often requires combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK achieves 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.",
keywords = "Informatics, Business informatics",
author = "Ricardo Usbeck and Ngomo, {Axel Cyrille Ngonga} and Lorenz B{\"u}hmann and Christina Unger",
note = "This work has been supported by the ESF, the Free State of Saxony and the FP7 project GeoKnow (GA No. 318159) Publisher Copyright: {\textcopyright} Springer International Publishing Switzerland 2015.; 12th European Semantic Web Conference - ESWC 2015, ESWC 2015 ; Conference date: 31-05-2015 Through 04-06-2015",
year = "2015",
month = jan,
day = "1",
doi = "10.1007/978-3-319-18818-8_22",
language = "English",
isbn = "978-3-319-18817-1",
series = "Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)",
publisher = "Springer Nature Switzerland AG",
pages = "353--368",
editor = "Fabien Gandon and Harald Sack and Antoine Zimmermann and Marta Sabou and Claudia d{\textquoteright}Amato and Philippe Cudr{\'e}-Mauroux",
booktitle = "The Semantic Web",
address = "Switzerland",
url = "https://2015.eswc-conferences.org/index.html, https://2015.eswc-conferences.org/call-challenges.html",

}

RIS

TY - CHAP

T1 - HAWK - hybrid question answering using linked data

AU - Usbeck, Ricardo

AU - Ngomo, Axel Cyrille Ngonga

AU - Bühmann, Lorenz

AU - Unger, Christina

N1 - Conference code: 12

PY - 2015/1/1

Y1 - 2015/1/1

N2 - The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often requires combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK achieves 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.

AB - The decentral architecture behind the Web has led to pieces of information being distributed across data sources with varying structure. Hence, answering complex questions often requires combining information from structured and unstructured data sources. We present HAWK, a novel entity search approach for Hybrid Question Answering based on combining Linked Data and textual data. The approach uses predicate argument representations of questions to derive equivalent combinations of SPARQL query fragments and text queries. These are executed so as to integrate the results of the text queries into SPARQL and thus generate a formal interpretation of the query. We present a thorough evaluation of the framework, including an analysis of the influence of entity annotation tools on the generation process of the hybrid queries and a study of the overall accuracy of the system. Our results show that HAWK achieves 0.68 respectively 0.61 F-measure within the training respectively test phases on the Question Answering over Linked Data (QALD-4) hybrid query benchmark.

KW - Informatics

KW - Business informatics

UR - http://www.scopus.com/inward/record.url?scp=84937407730&partnerID=8YFLogxK

UR - https://www.mendeley.com/catalogue/c03135ec-f5c6-3f8e-b1a3-5d8cd6c954f8/

U2 - 10.1007/978-3-319-18818-8_22

DO - 10.1007/978-3-319-18818-8_22

M3 - Article in conference proceedings

AN - SCOPUS:84937407730

SN - 978-3-319-18817-1

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

SP - 353

EP - 368

BT - The Semantic Web

A2 - Gandon, Fabien

A2 - Sack, Harald

A2 - Zimmermann, Antoine

A2 - Sabou, Marta

A2 - d’Amato, Claudia

A2 - Cudré-Mauroux, Philippe

PB - Springer Nature Switzerland AG

T2 - 12th European Semantic Web Conference - ESWC 2015

Y2 - 31 May 2015 through 4 June 2015

ER -