Open AccessSystematic review of question answering over knowledge bases
Author(s) -
Pereira Arnaldo,
Trifan Alina,
Lopes Rui Pedro,
Oliveira José Luís
Publication year - 2022
Publication title -
iet software
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 0.305
H-Index - 43
eISSN - 1751-8814
pISSN - 1751-8806
DOI - 10.1049/sfw2.12028
Subject(s) - computer science , question answering , field (mathematics) , semantic web , information retrieval , systematic review , inclusion (mineral) , natural language , knowledge base , data science , world wide web , knowledge management , artificial intelligence , gender studies , mathematics , medline , sociology , political science , pure mathematics , law
Over the years, a growing number of semantic data repositories have been made available on the web. However, this has created new challenges in exploiting these resources efficiently. Querying services require knowledge beyond the typical user’s expertise, which is a critical issue in adopting semantic information solutions. Several proposals to overcome this difficulty have suggested using question answering (QA) systems to provide user‐friendly interfaces and allow natural language use. Because question answering over knowledge bases (KBQAs) is a very active research topic, a comprehensive view of the field is essential. The purpose of this study was to conduct a systematic review of methods and systems for KBQAs to identify their main advantages and limitations. The inclusion criteria rationale was English full‐text articles published since 2015 on methods and systems for KBQAs. Sixty‐six articles were reviewed to describe their underlying reference architectures.