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One-Match and All-Match Categories for Keywords Matching in Chatbot | Science Publications

机译：Chatbot中关键字匹配的一次匹配和全部匹配类别科学出版物

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> Problem statement: Artificial intelligence chatbot is a technology that makes interactions between men and machines using natural language possible. From literature of chatbots keywords/pattern matching techniques, potential issues for improvement had been discovered. The discovered issues are in the context of keywords arrangement for matching precedence and keywords variety for matching flexibility. Approach: Combining previous techniques/mechanisms with some additional adjustment, new technique to be used for keywords matching process is proposed. Using newly developed chatbot named ViDi (abbreviation for Virtual Diabetes physician which is a chatbot for diabetes education activity) as a testing medium, the proposed technique named One-Match and All-Match Categories (OMAMC) is being used to test the creation of possible keywords surrounding one sample input sentence. The result for possible keywords created by this technique then being compared to possible keywords created by previous chatbots techniques surrounding the same sample sentence in matching precedence and matching flexibility context. Results: OMAMC technique is found to be improving previous matching techniques in matching precedence and flexibility context. This improvement is seen to be useful for shortening matching time and widening matching flexibility within the chatbots keywords matching process. Conclusion: OMAMC for keywords matching in chatbot is shown to be an improvement over previous techniques in the context of keywords arrangement for matching precedence and keywords variety for matching flexibility.
机译： > 问题陈述：人工智能聊天机器人是一项使使用自然语言的人与机器之间的交互成为可能的技术。从聊天机器人关键字/模式匹配技术的文献中，已经发现了潜在的改进问题。发现的问题是在关键字排列（用于匹配优先级）和关键字变体（用于匹配灵活性）的上下文中。 方法：结合先前的技术/机制和一些额外的调整，提出了一种用于关键字匹配过程的新技术。使用名为ViDi（虚拟糖尿病医师的缩写，是糖尿病教育活动的聊天机器人）的新开发的聊天机器人作为测试介质，提议的名为“单匹配和全匹配类别”（OMAMC）的技术被用于测试可能的创建。围绕一个示例输入句子的关键字。然后将通过此技术创建的可能关键字的结果与在匹配优先级和匹配灵活性上下文中围绕相同样本句子的以前的聊天机器人技术创建的可能关键字进行比较。 结果：发现OMAMC技术在匹配优先级和灵活性方面改善了以前的匹配技术。可以看出，这种改进对于缩短聊天机器人关键字匹配过程中的匹配时间和扩大匹配灵活性很有用。 结论：针对聊天机器人中关键字匹配的OMAMC在与优先级匹配的关键字排列和针对匹配灵活性的关键字变体方面被证明是对先前技术的改进。

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