Survey on challenges of Question Answering in the Semantic Web
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Survey on challenges of Question Answering in the Semantic Web. / Höffner, Konrad; Walter, Sebastian; Marx, Edgard et al.
In: Semantic Web, Vol. 8, No. 6, 2017, p. 895-920.Research output: Journal contributions › Journal articles › Research › peer-review
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TY - JOUR
T1 - Survey on challenges of Question Answering in the Semantic Web
AU - Höffner, Konrad
AU - Walter, Sebastian
AU - Marx, Edgard
AU - Usbeck, Ricardo
AU - Lehmann, Jens
AU - Ngonga Ngomo, Axel Cyrille
N1 - Publisher Copyright: © 2017 - IOS Press and the authors. All rights reserved.
PY - 2017
Y1 - 2017
N2 - Semantic Question Answering (SQA) removes two major access requirements to the Semantic Web: the mastery of a formal query language like SPARQL and knowledge of a specific vocabulary. Because of the complexity of natural language, SQA presents difficult challenges and many research opportunities. Instead of a shared effort, however, many essential components are redeveloped, which is an inefficient use of researcher's time and resources. This survey analyzes 62-different SQA systems, which are systematically and manually selected using predefined inclusion and exclusion criteria, leading to 72-selected publications out of 1960 candidates. We identify common challenges, structure solutions, and provide recommendations for future systems. This work is based on publications from the end of 2010 to July 2015 and is also compared to older but similar surveys.
AB - Semantic Question Answering (SQA) removes two major access requirements to the Semantic Web: the mastery of a formal query language like SPARQL and knowledge of a specific vocabulary. Because of the complexity of natural language, SQA presents difficult challenges and many research opportunities. Instead of a shared effort, however, many essential components are redeveloped, which is an inefficient use of researcher's time and resources. This survey analyzes 62-different SQA systems, which are systematically and manually selected using predefined inclusion and exclusion criteria, leading to 72-selected publications out of 1960 candidates. We identify common challenges, structure solutions, and provide recommendations for future systems. This work is based on publications from the end of 2010 to July 2015 and is also compared to older but similar surveys.
KW - Question Answering
KW - Semantic Web
KW - survey
KW - Informatics
KW - Business informatics
UR - http://www.scopus.com/inward/record.url?scp=85027403246&partnerID=8YFLogxK
U2 - 10.3233/SW-160247
DO - 10.3233/SW-160247
M3 - Journal articles
AN - SCOPUS:85027403246
VL - 8
SP - 895
EP - 920
JO - Semantic Web
JF - Semantic Web
SN - 1570-0844
IS - 6
ER -