• Journal of KIISE:Computing Practices and Letters
• /
• v.10 no.1
• /
• pp.89-98
• /
• 2004

Conversational agent is a system that provides users with proper information and maintains the context of dialogue on the natural language. Analyzing and modeling process of user's query is essential to make it more realistic, for which Bayesian network is a promising technique. When experts design the network for a domain, the network is usually very complicated and is hard to be understood. The separation of variables in the domain reduces the size of networks and makes it easy to design the conversational agent. Composing Bayesian network as two stages, we aim to design conversational agent easily and analyze user's query in detail. Also, previous information of dialogue makes it possible to maintain the context of conversation. Actually implementing it for a guide of web pages, we can confirm the usefulness of the proposed architecture for conversational agent.

• The Journal of the Convergence on Culture Technology
• /
• v.8 no.1
• /
• pp.565-576
• /
• 2022

The scope and functions of a conversational agent are gradually expanding. In particular, research and technology development is being conducted on a conversational agent that can speak first without user calls. However, still in its early stages, there is a lack of research on how a preceded utterance conversational agent will affect users. Accordingly, this study conducted a 2×3 mixed design using the user's task performance condition and the agent's self-exposure as independent variables and measured Intimacy, Functional Satisfaction, Psychological Reactance, and Workload as dependent variables to identify the effects of preceded utterance conversational agent on user experience.

• Archives of design research
• /
• v.16 no.1
• /
• pp.117-126
• /
• 2003

The human computer interaction has gone through diverse changes along with the technical progress of computers. With the spread of the world wide web, attempts of various forms and methods of interactions reflecting the characteristics of the web are being made. Among the diverse concepts of interaction, Conversational Agent uses a character as the visual perceptional object and through the interaction based on conversation it suggests a natural, human, intuitive interaction. In this study, Conversational Agent was suggested and applied on a cyber lecture website and the appropriateness was verified. The fundamental structure and method needed in constructing a conversation was examined through the study on conversation. After that the characteristics of the conversation used on the web was identified and hereby and the coherence and conversation structure was deducted. After the characteristics of the conversational agent were observed, it was applied to the previously deducted web sites logical connection and conversation structure. Lastly, the conversational agent suitable for the web site was proposed and realized.

• Journal of the Korea Society of Computer and Information
• /
• v.13 no.6
• /
• pp.263-271
• /
• 2008

This paper presents a Korean conversational agent system in a mobile environment using natural language processing techniques. The aim of a conversational agent in mobile environment is to provide natural language interface and enable more natural interaction between a human and an agent. Constructing such an agent, it is required to develop various natural language understanding components and effective utterance generation methods. To understand spoken style utterance, we perform morphosyntactic analysis, shallow semantic analysis including modality classification and predicate argument structure analysis, and to generate a system utterance, we perform example based search which considers lexical similarity, syntactic similarity and semantic similarity.

• Journal of the Korea Society of Computer and Information
• /
• v.28 no.1
• /
• pp.27-38
• /
• 2023

In this paper, we propose a conversational AI agent based on continual learning that can continuously learn and grow with new data over time. A continual learning-based conversational AI agent consists of three main components: Task manager, User attribute extraction, and Auto-growing knowledge graph. When a task manager finds new data during a conversation with a user, it creates a new task with previously learned knowledge. The user attribute extraction model extracts the user's characteristics from the new task, and the auto-growing knowledge graph continuously learns the new external knowledge. Unlike the existing conversational AI agents that learned based on a limited dataset, our proposed method enables conversations based on continuous user attribute learning and knowledge learning. A conversational AI agent with continual learning technology can respond personally as conversations with users accumulate. And it can respond to new knowledge continuously. This paper validate the possibility of our proposed method through experiments on performance changes in dialogue generation models over time.

• Journal of the HCI Society of Korea
• /
• v.12 no.1
• /
• pp.15-23
• /
• 2017

Applying the concept and components of human nature to the conversational agent in the smart home context, this study investigated the effects of the level of anthropomorphism and interaction type on the emotional user experiences and future use intention. The results of experiment study showed that the high-low condition of anthropomorphism and the voice-chatting interaction type have impacts on the perceived closeness, likability, and future use intention. That is, people evaluate the conversational agent as more close, likable, and useful when they perceive more human nature components and when in the voice interaction mode. Psychological resistance was lower in the voice than in the chatting mode regardless of the level of anthropomorphism. The results also demonstrated an interaction effect of anthropomorphism and interaction type on the future use intention: the effect of anthropomorphism existed only in the voice interaction mode. It leads to the conclusion that a conversational agent with the voice recognition interface should be designed with the higher level of human nature components for the continuous use.

• Journal of Digital Convergence
• /
• v.20 no.2
• /
• pp.251-260
• /
• 2022

Despite the development of technology and the increase in the spread of smart speakers, user satisfaction keeps decreasing due to conversational errors. This study aims to examine the effect of the self-repair strategy on user experience in the context of conversational agents of smart speakers. Scenarios were designed based on error situations, and participants were divided into two groups by task criticality. The results revealed that the agent's self-repair strategy has a negative effect on trust and perceived ease of use compared with performance without error. It also influenced adoption intention through interaction with task criticality. This study is significant in that it empirically investigated the effects of the self-repair strategy and the user experience factors related to the actual acceptance of the self-repair strategy.

• 한국HCI학회:학술대회논문집
• /
• 2008.02a
• /
• pp.178-183
• /
• 2008

The goal of this study is finding flow-map in conversation what is going on user and embodied conversational agent by analysing that conversation. Specifically, this study not only find elements of conversation, but also draw out patterns of conversation can be exist for dialogue ability between user and Embodied conversational agent. To do this, we collect data through in-depth one to one interview, and then we analysis collected data to try to find out element of user-agent conversation based on qualitative research refer to the theory of conversation analytics and type of conversation. As a result, six flow map is deducted Especially, the irregular conversation is hard to find in human-human conversation, and the frequency is the most in data. In addition, when elements of interruption came out, be hostile to partner or correct the press conversation. This study can have positive effect to embodied conversation agent developer, user and service offerer because this study find the type of conversation through analysis that between embodied conversational agent and user.

• Journal of KIISE:Computing Practices and Letters
• /
• v.9 no.5
• /
• pp.530-540
• /
• 2003

As the amount of information on Internet sites increases, it becomes more necessary to provide information in efficient ways. However, information search methods based on Boolean combination of keywords that most sites provide are difficult to express user's intention adequately so that there are numerous unexpected search results. This paper proposes a conversational agent that provides users with accurate information in a friendly manner through natural language conversation. The agent recognizes user's intention by applying finite state automata to natural language queries, utilizes the intention for structured pattern matching with response knowledge, and thus provides answers that are robust against changes in word order and consistent with the user's intention. To show its practical utility, the agent is applied to the problem of introducing a Web site. The results show that the conversational agent has the ability to provide accurate and friendly responses.

• Journal of KIISE:Software and Applications
• /
• v.33 no.10
• /
• pp.877-885
• /
• 2006

Recently it is proposed that the Bayesian networks used as conversational agent for topic inference is useful but the Bayesian networks require much time to model, and the Bayesian networks also have to be modified when the scripts, the database for conversation, are added or modified and this hinders the scalability of the agent. This paper presents a method to improve the scalability of the agent by constructing the Bayesian network from scripts automatically. The proposed method is to model the structure of Bayesian networks hierarchically and to utilize Noisy-OR gate to form the conditional probability distribution table (CPT). Experimental results with ten subjects confirm the usefulness of the proposed method.