Interactive Question Answering Systems: Literature Review

Author:

Biancofiore Giovanni Maria1ORCID,Deldjoo Yashar2ORCID,Noia Tommaso Di2ORCID,Di Sciascio Eugenio1ORCID,Narducci Fedelucio2ORCID

Affiliation:

1. Polytechnic University of Bari, Bari, Italy

2. Politecnico di Bari, Bari, Italy

Abstract

Question-answering systems are recognized as popular and frequently effective means of information seeking on the web. In such systems, information seekers can receive a concise response to their queries by presenting their questions in natural language. Interactive question answering is a recently proposed and increasingly popular solution that resides at the intersection of question answering and dialogue systems . On the one hand, the user can ask questions in normal language and locate the actual response to her inquiry; on the other hand, the system can prolong the question-answering session into a dialogue if there are multiple probable replies, very few, or ambiguities in the initial request. By permitting the user to ask more questions, interactive question answering enables users to interact with the system and receive more precise results dynamically. This survey offers a detailed overview of the interactive question-answering methods that are prevalent in current literature. It begins by explaining the foundational principles of question-answering systems, hence defining new notations and taxonomies to combine all identified works inside a unified framework. The reviewed published work on interactive question-answering systems is then presented and examined in terms of its proposed methodology, evaluation approaches, and dataset/application domain. We also describe trends surrounding specific tasks and issues raised by the community, so shedding light on the future interests of scholars. Our work is further supported by a GitHub page synthesizing all the major topics covered in this literature study. https://sisinflab.github.io/interactive-question-answering-systems-survey/

Publisher

Association for Computing Machinery (ACM)

Reference174 articles.

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3. Francesca Alloatti, Luigi Di Caro, and Gianpiero Sportelli. 2019. Real life application of a question answering system using BERT language model. In SIGdial. Association for Computational Linguistics, 250–253.

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5. Stanislaw Antol, Aishwarya Agrawal, Jiasen Lu, Margaret Mitchell, Dhruv Batra, C. Lawrence Zitnick, and Devi Parikh. 2015. VQA: Visual question answering. In ICCV. 2425–2433.

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