A Review of Question Answering Systems

  • Bolanle Ojokoh Department of Information Systems, Federal University of Technology, Akure, Nigeria
  • Emmanuel Adebisi Department of Computer Science, Federal University of Technology, Akure, Nigeria
Keywords: Question Analysis, Answer Extraction, Information Retrieval, Classification, Review


Question Answering (QA) targets answering questions defined in natural language. Question Answering Systems offer an automated approach to procuring solutions to queries expressed in natural language. A lot of QA surveys have classified Question Answering systems based on different criteria such as queries inquired by users, features of data bases used, nature of generated answers, question answering approaches and techniques. To fully understand QA systems, how it has grown into its current QA needs, and the need to scale up to meet future expectations, a broader survey of QA systems becomes essential. Hence, in this paper, we take a short study of the generic QA framework vis a vis Question Analysis, Passage Retrieval and Answer Extraction and some important issues associated with QA systems. These issues include Question Processing, Question Classes, Data Sources for QA, Context and QA, Answer Extraction, Real time Question Answering, Answer Formulation, Multilingual (or cross-lingual) question answering, Advanced reasoning for QA, Interactive QA, User profiling for QA and Information clustering for QA. Finally, we classify QA systems based on some identified criteria in literature. These include Application domain, Question type, Data source, Form of answer generated, Language paradigm and Approaches. We subsequently made an informed judgment of the basis for each classification criterion through literature on QA systems.


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Author Biographies

Bolanle Ojokoh, Department of Information Systems, Federal University of Technology, Akure, Nigeria

Bolanle Ojokoh holds B.Sc, M.Tech and Ph.D degrees in Computer Science. She is currently an Associate Professor in Information Systems of the Federal University of Technology, Akure (FUTA), Nigeria. She is a member of some professional bodies including Organization of Women in Science for the Developing World (OWSD) and Association of Computing Machinery (ACM). She has mentored more than ten Masters theses to completion and is currently supervising some Masters and Ph.D students. Her current research interests include Question Answering, Information Retrieval, Filtering and Extraction, Recommender Systems, and Gender issues in Science and Information Technology. She was awarded TWAS Young Affiliate in July 2013 and is currently and an Executive Board Member of the TWAS Young Affiliate Network (TYAN).

Emmanuel Adebisi, Department of Computer Science, Federal University of Technology, Akure, Nigeria

Emmanuel Adebisi is a Ph.D. student at the Federal University of Technology, Akure since March 2019. He attended Joseph Ayo Babalola University, Osun state Nigeria where he received his B.Sc. in Computer Science in 2014. Emmanuel obtained his M.Tech. in Computer Science from Federal University of Technology, Akure Ondo state, Nigeria in 2018. Emmanuel is a software developer and works as a consultant to IT Firms. He is also the C.E.O of Techatrek (a tech company he started in 2014). He worked as a Teaching Assistant at Federal College of Education (Special) Oyo (2014–2015) and Federal University of Technology Akure from (2016–2018). His Ph.D. work centers on Automatic Question Answering Systems.


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