A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services

Chatbot technologies have made our lives easier. To create a chatbot with high intelligence, a significant amount of knowledge processing is required. However, this can slow down the reaction time; hence, a mechanism to enable a quick response is needed. This paper proposes a cache mechanism to impr...

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Autores principales:	Ozoda Makhkamova, Doohyun Kim
Formato:	article
Lenguaje:	EN
Publicado:	MDPI AG 2021
Materias:	chatbot multi-layer service cache mechanism response time chatbot cache Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
Acceso en línea:	https://doaj.org/article/a35f0d76c0d94134a66ac8affe858a94
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id	oai:doaj.org-article:a35f0d76c0d94134a66ac8affe858a94
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spelling	oai:doaj.org-article:a35f0d76c0d94134a66ac8affe858a942021-11-11T15:04:10ZA Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services10.3390/app112199812076-3417https://doaj.org/article/a35f0d76c0d94134a66ac8affe858a942021-10-01T00:00:00Zhttps://www.mdpi.com/2076-3417/11/21/9981https://doaj.org/toc/2076-3417Chatbot technologies have made our lives easier. To create a chatbot with high intelligence, a significant amount of knowledge processing is required. However, this can slow down the reaction time; hence, a mechanism to enable a quick response is needed. This paper proposes a cache mechanism to improve the response time of the chatbot service; while the cache in CPU utilizes the locality of references within binary code executions, our cache mechanism for chatbots uses the frequency and relevance information which potentially exists within the set of Q&A pairs. The proposed idea is to enable the broker in a multi-layered structure to analyze and store the keyword-wise relevance of the set of Q&A pairs from chatbots. In addition, the cache mechanism accumulates the frequency of the input questions by monitoring the conversation history. When a cache miss occurs, the broker selects a chatbot according to the frequency and relevance, and then delivers the query to the selected chatbot to obtain a response for answer. This mechanism showed a significant increase in the cache hit ratio as well as an improvement in the average response time.Ozoda MakhkamovaDoohyun KimMDPI AGarticlechatbotmulti-layer servicecache mechanismresponse timechatbot cacheTechnologyTEngineering (General). Civil engineering (General)TA1-2040Biology (General)QH301-705.5PhysicsQC1-999ChemistryQD1-999ENApplied Sciences, Vol 11, Iss 9981, p 9981 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	chatbot multi-layer service cache mechanism response time chatbot cache Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999
spellingShingle	chatbot multi-layer service cache mechanism response time chatbot cache Technology T Engineering (General). Civil engineering (General) TA1-2040 Biology (General) QH301-705.5 Physics QC1-999 Chemistry QD1-999 Ozoda Makhkamova Doohyun Kim A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
description	Chatbot technologies have made our lives easier. To create a chatbot with high intelligence, a significant amount of knowledge processing is required. However, this can slow down the reaction time; hence, a mechanism to enable a quick response is needed. This paper proposes a cache mechanism to improve the response time of the chatbot service; while the cache in CPU utilizes the locality of references within binary code executions, our cache mechanism for chatbots uses the frequency and relevance information which potentially exists within the set of Q&A pairs. The proposed idea is to enable the broker in a multi-layered structure to analyze and store the keyword-wise relevance of the set of Q&A pairs from chatbots. In addition, the cache mechanism accumulates the frequency of the input questions by monitoring the conversation history. When a cache miss occurs, the broker selects a chatbot according to the frequency and relevance, and then delivers the query to the selected chatbot to obtain a response for answer. This mechanism showed a significant increase in the cache hit ratio as well as an improvement in the average response time.
format	article
author	Ozoda Makhkamova Doohyun Kim
author_facet	Ozoda Makhkamova Doohyun Kim
author_sort	Ozoda Makhkamova
title	A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
title_short	A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
title_full	A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
title_fullStr	A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
title_full_unstemmed	A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services
title_sort	conversation history-based q&a cache mechanism for multi-layered chatbot services
publisher	MDPI AG
publishDate	2021
url	https://doaj.org/article/a35f0d76c0d94134a66ac8affe858a94
work_keys_str_mv	AT ozodamakhkamova aconversationhistorybasedqacachemechanismformultilayeredchatbotservices AT doohyunkim aconversationhistorybasedqacachemechanismformultilayeredchatbotservices AT ozodamakhkamova conversationhistorybasedqacachemechanismformultilayeredchatbotservices AT doohyunkim conversationhistorybasedqacachemechanismformultilayeredchatbotservices
_version_	1718437161537110016

A Conversation History-Based Q&A Cache Mechanism for Multi-Layered Chatbot Services

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