Open AccessSystematic mapping study on question answering frameworks over linked data
Author(s) -
Tasar Ceren Ocal,
Komesli Murat,
Unalir Murat Osman
Publication year - 2018
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/iet-sen.2018.5105
Subject(s) - computer science , question answering , set (abstract data type) , sentence , point (geometry) , information retrieval , inclusion (mineral) , data science , natural language processing , psychology , social psychology , geometry , mathematics , programming language
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.