An architectural design of Virtual Dietitian (ViDi) for diabetic patients

Lokman, Abbas Saliimi; Zain, Jasni Mohamad

doi:10.1109/iccsit.2009.5234671

Cited by 15 publications

(26 citation statements)

References 3 publications

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“…For example, AIML, which is the technique first used with the ALICE Chatbot, is used to build the Chatbots in [5], [10], and [26], while SQL (or RDB) is used in [24] and [25]. Both AIML and SQL are used in [22] and [23]. Neither AIML or SQL are used in [9] and [27].…”

Section: Discussionmentioning

confidence: 99%

“…New Chatbots have been created in [5], [9], [23], and [27], which add new techniques or use improved previous designs. Also new techniques, algorithms or extensions have been added to existing Chatbots in [10], [22], [24], [25], and [26] in order to improve their function or extend available software by adding chat interaction.…”

Section: Discussionmentioning

confidence: 99%

“…Again Malaysian is used. The extension of ViDi designed in [23] makes it available to users on the internet through a web browser.…”

Section: Speech Analysis and Responsementioning

confidence: 99%

“…In [23] the authors presented the Chatbot ViDi (Virtual Dietician) that interacts with diabetic patients as a virtual adviser. The authors proposed a special design for the Chatbot ViDi to make it remember the conversational paths taken during the question and answer session.…”

Section: Speech Analysis and Responsementioning

confidence: 99%

“…The authors in [25] proposed a new technique for keyword matching using ViDi, ( [23] and updated in [24]) as a test environment. The proposed technique is called One Match or All Match Categories (OMAMC).…”

Section: Speech Analysis and Responsementioning

confidence: 99%

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Survey on Chatbot Design Techniques in Speech Conversation Systems

Abdul-Kader¹,

Woods²

2015

ijacsa

175

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Abstract-Human-Computer Speech is gaining momentum as a technique of computer interaction. There has been a recent upsurge in speech based search engines and assistants such as Siri, Google Chrome and Cortana. Natural Language Processing (NLP) techniques such as NLTK for Python can be applied to analyse speech, and intelligent responses can be found by designing an engine to provide appropriate human like responses. This type of programme is called a Chatbot, which is the focus of this study. This paper presents a survey on the techniques used to design Chatbots and a comparison is made between different design techniques from nine carefully selected papers according to the main methods adopted. These papers are representative of the significant improvements in Chatbots in the last decade. The paper discusses the similarities and differences in the techniques and examines in particular the Loebner prizewinning Chatbots.

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Section: Discussionmentioning

confidence: 99%

Section: Discussionmentioning

confidence: 99%

“…Again Malaysian is used. The extension of ViDi designed in [23] makes it available to users on the internet through a web browser.…”

Section: Speech Analysis and Responsementioning

confidence: 99%

Section: Speech Analysis and Responsementioning

confidence: 99%

Section: Speech Analysis and Responsementioning

confidence: 99%

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Survey on Chatbot Design Techniques in Speech Conversation Systems

Abdul-Kader¹,

Woods²

2015

ijacsa

175

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Chatbots: Security, privacy, data protection, and social aspects

Hasal

Nowaková

Saghair

et al. 2021

Concurrency and Computation

121

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Chatbots are artificial communication systems becoming increasingly popular and not all their security questions are clearly solved. People use chatbots for assistance in shopping, bank communication, meal delivery, healthcare, cars, and many other actions.However, it brings an additional security risk and creates serious security challenges which have to be handled. Understanding the underlying problems requires defining the crucial steps in the techniques used to design chatbots related to security. There are many factors increasing security threats and vulnerabilities. All of them are comprehensively studied, and security practices to decrease security weaknesses are presented. Modern chatbots are no longer rule-based models, but they employ modern natural language and machine learning techniques. Such techniques learn from a conversation, which can contain personal information. The paper discusses circumstances under which such data can be used and how chatbots treat them. Many chatbots operate on a social/messaging platform, which has their terms and conditions about data. The paper aims to present a comprehensive study of security aspects in communication with chatbots. The article could open a discussion and highlight the problems of data storage and usage obtained from the communication user-chatbot and propose some standards to protect the user. K E Y W O R D Schat, chatbots, data protection, GDPR, security, virtual assistants * A bot is sometimes referred to as a chatbot, but to be precise, a bot is a computer program (tool) that automates processes. A chatbot is a sub-genre of the bot environment with a focus on talking or conversation. Some companies instead of Chatbot use the name 'Conversational AI' or ' AI chatbots' to highlight that their chatbot is powered by machine learning and information retrieval techniques. In this article the term 'chatbot' is used for all types of chatbots.This is an open access article under the terms of the Creative Commons Attribution-NonCommercial-NoDerivs License, which permits use and distribution in any medium, provided the original work is properly cited, the use is non-commercial and no modifications or adaptations are made.

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Self-Anamnesis with a Conversational User Interface: Concept and Usability Study

et al. 2018

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Objective Self-anamnesis is a procedure in which a patient answers questions about the personal medical history without interacting directly with a doctor or medical assistant. If collected digitally, the anamnesis data can be shared among the health care team. In this article, we introduce a concept for digital anamnesis collection and assess the applicability of a conversational user interface (CUI) for realizing a mobile self-anamnesis application. Materials and Methods We implemented our concept for self-anamnesis for the concrete field of music therapy. We collected requirements with respect to the application from music therapists and by reviewing the literature. A rule-based approach was chosen for realizing the anamnesis conversation between the system and the user. The Artificial Intelligence Markup Language was exploited for encapsulating the questions and responses of the system. For studying the quality of the system and analyzing performance, humanity, effect, and accessibility of the system, we performed a usability test with 22 persons. Results The current version of the self-anamnesis application is equipped with 63 questions on the music biography of a patient that are asked subsequently to the user by means of a chatbot conversation. The usability study showed that a CUI is a practical way for collecting anamnesis data. Users felt engaged of answering the questions and liked the human characteristics of the chatbot. They suggested to extend the conversation capabilities of the chatbot so that the system can react appropriately, in particular when the user is not feeling well. Conclusions We could demonstrate the applicability of a CUI for collecting anamnesis data. In contrast to digital anamnesis questionnaires, the application of a CUI provides several benefits: the user can be encouraged to complete all queries and can ask clarifying questions in case something is unclear.

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An architectural design of Virtual Dietitian (ViDi) for diabetic patients

Cited by 15 publications

References 3 publications

Survey on Chatbot Design Techniques in Speech Conversation Systems

Survey on Chatbot Design Techniques in Speech Conversation Systems

Chatbots: Security, privacy, data protection, and social aspects

Self-Anamnesis with a Conversational User Interface: Concept and Usability Study

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