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

APPLIED SCIENCES-BASEL(2021)SCI 4区

Konkuk Univ

Cited 1|Views1
Abstract
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.
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chatbot,multi-layer service,cache mechanism,response time,chatbot cache
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Chat Paper

要点】:本文提出了一种基于对话历史的问答缓存机制,以改善多层聊天服务的响应时间,通过分析并存储关键词相关的问答对,并监控对话历史累积输入问题频率,有效提高缓存命中率及平均响应时间。

方法】:通过在多层结构中的代理(broker)分析并存储关键词相关的问答对,并利用对话历史记录来累积问题的频率,从而优化聊天机器人的响应速度。

实验】:实验采用自定义的对话历史数据,通过实施所提缓存机制,观察到缓存命中率显著提升以及平均响应时间的改善。