A survey on non-factoid question answering systems

• Published in: International journal of computers & applications 2022-09, Vol.44 (9), p.830-837
• Main Authors: Breja, Manvi, Jain, Sanjay Kumar
• Format: Article
• Language: English
• Subjects: answer extraction; answer re-ranker; document retrieval; Modules; natural language processing; Non-factoid question answering system; question analysis; Questions
• ISSN: 1206-212X; 1925-7074
• DOI: 10.1080/1206212X.2021.1949117

Question Answering System (QAS) aims at providing the most appropriate answer to the user's question asked in any natural language. It emerged as a future of web search that crawls structured and unstructured collections of documents to find answers. A lot of research has already been done on answering factoid questions and achieved promising accuracy, whereas non-factoid question answering is a challenging task and explores newer avenues for fact-finding and analysis. The research on handling different modules of non-factoid question answering has drastically increased from 2012 which evokes the need for summarizing and providing a comprehensive analysis of the work that has already been done in this field. The survey identifies different challenges faced in each module, how they have been addressed by the researchers with their advantages or disadvantages and further improvements. The survey is written with an objective to help the researchers understand the field with how it has been undertaken by different approaches with their impact on performance. The paper finally concludes by investigating research gaps and research objectives that are promising to get an insight into future research directions.