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Question Answering Chatbot for Troubleshooting Queries based on Transfer Learning

Zeeshan Haque Syed, Asma Trabelsi, Emmanuel Helbert, Vincent Bailleau, Christian Muths

2021Procedia Computer Science17 citationsDOIOpen Access PDF

Abstract

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.

Topics & Concepts

HaystackTroubleshootingComputer scienceInformation retrievalContext (archaeology)Question answeringWorld Wide WebFocus (optics)Open domainSet (abstract data type)Operating systemOpticsProgramming languagePhysicsBiologyPaleontologyTopic ModelingMultimodal Machine Learning ApplicationsDomain Adaptation and Few-Shot Learning
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