Systematic mapping study on question answering frameworks over linked data

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Date

2018

Authors

Ceren Ocal Tasar
Murat Komesli
Murat Osman Unalir

Journal Title

Journal ISSN

Volume Title

Publisher

Institution of Engineering and Technology journals@theiet.org

Open Access Color

GOLD

Green Open Access

No

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No
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Abstract

Employing linked data technologies and semantic endpoints for question answering systems are expanding approaches among the researchers. Therefore systems that combine syntactic and semantic analysis and enrich input questions by sentence-level recognition are examined. A systematic mapping study is conducted to identify and analyse the studies from major databases journals and proceedings of conferences or workshops published between 2010 and 2017. With a set of 14 research questions inclusion and exclusion criteria are specified. 53 studies are selected as primary studies from an initial set of 845 papers. This study provides a mapping while focusing on the methods and identifying the gaps between required and existing approaches. Popular approaches which have gained the most attention among researchers are given as a conclusion. Moreover a comparison between the authors' study and related work in the literature is given to point out the differences and the contributions of their study. As the result of the comparison it is concluded that the study is a novel and original topic on question answering frameworks. © 2019 Elsevier B.V. All rights reserved.

Description

Keywords

Data Handling, Mapping, Semantics, Data Technologies, Inclusion And Exclusions, Question Answering, Question Answering Systems, Research Questions, Semantic Analysis, Sentence Level, Systematic Mapping Studies, Linked Data, Data handling, Mapping, Semantics, Data technologies, Inclusion and exclusions, Question Answering, Question answering systems, Research questions, Semantic analysis, Sentence level, Systematic mapping studies, Linked data, Linked Data Technologies, Inclusion Criteria, Systematic Mapping, Natural Language Processing, Sentence-Level Recognition, Database Management Systems, Research Questions, Exclusion Criteria, Semantic Endpoints, Input Questions, Semantic Analysis, Ontologies (Artificial Intelligence), Question Answering Frameworks, Question Answering (Information Retrieval), Linked Data

Fields of Science

0202 electrical engineering, electronic engineering, information engineering, 02 engineering and technology

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OpenCitations Citation Count
2

Source

IET Software

Volume

12

Issue

6

Start Page

461

End Page

472
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CrossRef : 2

Scopus : 4

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Mendeley Readers : 14

SCOPUS™ Citations

4

checked on Apr 08, 2026

Web of Science™ Citations

3

checked on Apr 08, 2026

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