HAWK - hybrid question answering using linked data

Publikation: Beiträge in SammelwerkenAufsätze in KonferenzbändenForschungbegutachtet

Authors

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.

OriginalspracheEnglisch
TitelThe Semantic Web : Latest Advances and New Domains - 12th European Semantic Web Conference, ESWC 2015, Proceedings
HerausgeberFabien Gandon, Harald Sack, Antoine Zimmermann, Marta Sabou, Claudia d’Amato, Philippe Cudré-Mauroux
Anzahl der Seiten16
VerlagSpringer Nature Switzerland AG
Erscheinungsdatum01.01.2015
Seiten353-368
ISBN (Print)978-3-319-18817-1
ISBN (elektronisch)978-3-319-18818-8
DOIs
PublikationsstatusErschienen - 01.01.2015
Extern publiziertJa
Veranstaltung12th European Semantic Web Conference - ESWC 2015 - Portoroz, Slowenien
Dauer: 31.05.201504.06.2015
Konferenznummer: 12
https://2015.eswc-conferences.org/index.html
https://2015.eswc-conferences.org/call-challenges.html

Bibliographische Notiz

Funding Information:
This work has been supported by the ESF, the Free State of Saxony and the FP7 project GeoKnow (GA No. 318159).

Publisher Copyright:
© Springer International Publishing Switzerland 2015.

DOI

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