Question Answering Chatbot for Troubleshooting Queries based on Transfer Learning

Open-Domain Question Answering (ODQA) is a technique for finding an answer to a given query from a large set of documents. In this paper, we present an experimentation study to compare ODQA candidate solutions in the context of troubleshooting documents. We mainly focus on a well known open-source framework which is called Haystack. This framework comprises two key components which are the Retriever and the Reader. The Haystack Framework comes with several Retriever-Reader combinations and the choice of the best one is still unanswered till now. In this paper, we conduct an experimentation study to compare different Retriever-Reader combinations. Our aim is to come up with the best combination of components in regard to the speed and the processing power within the context of troubleshooting queries. (C) 2021 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://crativecommons.org/licenses/by-nc-nd/4.0) Peer-review under responsibility of the scientific committee of KES International.

Automated summary

This paper presents an experimentation study comparing different Retriever-Reader combinations in the context of troubleshooting documents, aiming to find the best combination of components for speed and processing power.