• Information Systems Review
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• v.19 no.4
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• pp.135-156
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• 2017

An intelligent personal assistant (IPA) is a software agent that assists people to perform basic tasks or services for an individual by commonly providing information via natural language. In spite of the versatile capabilities of the IPA to answer a user's simple information-based queries, such as the weather and driving directions, the actual usage rates for IPA services are limited to date. In this research, to evaluate the factors affecting the intention to use IPA, we develop an empirical model based on technology acceptance model, innovation diffusion theory, and IS success model. Afterward, we collect 203 questionnaires from actual users of IPAs. Finally, the structural equation model validates the causal relationship between the constructs of the model. Consequently, the innovation characteristics of IPA drawn from innovation diffusion theory, namely, relative advantage, compatibility, observability, all exerted a positive influence on perceived usefulness. Furthermore, information quality, a quality characteristic of IPA obtained from DeLone and McLean's IS success model, presented a positive effect on perceived usefulness and perceived ease of use. Finally, the perceived intelligence of IPA displayed a positive influence on perceived usefulness and ease of use. This characteristic was also a major factor that can increase the intention to use the IPA. Given these research findings, this study is significant for identifying factors that may influence the intention to use the IPA by providing strategic guidelines to relevant business operators and establishing an integrated model.

• Proceedings of the Korea Contents Association Conference
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• 2017.05a
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• pp.467-468
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• 2017

본 연구에서는 모바일 지능형 개인비서 서비스의 음성 사용자 인터페이스(Voice User Interface, VUI) 사용에 있어서 혁신저항요인을 연구한다.

• Science of Emotion and Sensibility
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• v.23 no.1
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• pp.69-78
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• 2020

This study compares and analyzes user experiences of intelligent personal assistant services based on the evaluation criteria of human-computer interaction to explore positive elements of user experiences and factors that could be improved. The research was conducted on Apple's Siri, Google's Google Associate, and Samsung's Bixby, which is presently the smartest personal assistant service on the market. The research method was to compare and analyze the concepts and characteristics of the current services through a literature review and by interviewing seven UI/UX design experts for the second 2 weeks using contextual inquiry. The interview reorganized Peter Morville's user experience honeycomb, reducing his seven usability principles down to five, asking questions about usability, convenience, visual attractiveness, reliability, and satisfaction. On the basis of the reconfigured usability principle, the assessment was conducted on the basis of the assessment timing and the system usability scale. This study is meaningful in that it analyzed the user experience of artificial intelligence personal assistant services both quantitatively and qualitatively.

• Journal of Digital Convergence
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• v.18 no.9
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• pp.379-389
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• 2020

This is a qualitative study about Google 'Nest Hub Max' that displays proactive intelligent personal assistant. Following the step of grounded theory, an in-depth interview for 6 users who had used this device for a month was taken. 186 concepts were discovered, categorized as 11 top-categories and 24 sub-categories. Paradigm diagram, considering axis-coding, was made and it have been narrowed down to 'Usage patterns' of proactive IPA, considering selective coding aspects. 'Usage patterns' were divided to passive and active user. Thus, neither passive user nor active user was satisfied about device and proactive IPA. This study is meaningful that it constructed basic data about the user experience of proactive IPA on this device. It will support the device or service that consists proactive IPA in the future.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.155-159
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• 2018

최근 화두가 되고있는 지능형 개인 비서 시스템에서 자연어 이해(NLU) 시스템은 중요한 구성요소이다. 자연어 이해 시스템은 사용자의 발화로부터 대화의 도메인(domain), 의도(intent), 의미적 슬롯(semantic slot)을 분류하는 역할을 한다. 하지만 자연어 이해 시스템을 학습하기 위해서는 많은 양의 라벨링 된 데이터를 필요로 하며 새로운 도메인으로 시스템을 확장할 때, 새롭게 데이터 라벨링을 진행해야 하는 한계점이 존재한다. 이를 해결하기 위해 본 연구는 적대 학습 방법을 이용하여 풍부한 양으로 구성된 기존(source) 도메인의 데이터부터 적은 양으로 라벨링 된 데이터로 구성된 대상(target) 도메인을 위한 슬롯 채우기(slot filling) 모델 학습 방법을 제안한다. 실험 결과 적대 학습을 적용할 경우, 적대 학습을 적용하지 않은 경우 보다 높은 f-1 score를 나타냄을 확인하였다.

• Knowledge Management Research
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• v.19 no.4
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• pp.99-118
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• 2018

Recently, individuals are interested in a variety of products and services based on artificial intelligence. Among those products and services, an intelligent personal assistants are attracting many attention from IT companies as a next generation platform. Thus, the main purpose of this study is to investigate effects of intelligent personal assistant's benefits on user's value formation and adoption behavior based on Value-based Adoption Model. In addition, the moderating effect of personal innovativeness is examined through empirical analysis. Based on the analysis with the data from actual users, the results show that usefulness, enjoyment, technicality and cost advantage have significant influences on perceived value and correspondingly have an effect on intention to adopt. Personal innovativeness is related to the relationship between perceived value and intention to adopt. These findings may provide important insights to the relevant field regarding the use and spread of intelligent personal assistants.

• Proceedings of the Korea Technology Innovation Society Conference
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• 2017.05a
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• pp.623-643
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• 2017

최근 인공지능 기술이 발달하면서 챗봇이 글로벌 IT기업들에게 새로운 IoT플랫폼으로 주목받고 있다. 챗봇이란 대화형 인터페이스 상에서 규칙 또는 인공지능(AI)을 이용해 사용자와 상호작용(interaction)을 하는 서비스를 지칭한다. 챗봇은 현재 간단한 정보검색 및 가상비서 서비스를 제공하는 수준이지만, 향후 IoT와 O2O 영역의 핵심적인 인공지능 플랫폼으로 부상할 전망이다. 챗봇은 스마트폰 디바이스와 어플리케이션을 기반으로 빠르게 확산되어 핵심 플랫폼의 지위를 차지할 것으로 예상된다. 그러나 챗봇 사용자의 수용행태에 관한 학술적 연구는 미비한 상황이다. 이에 본 연구는 기존의 기술수용이론(TAM)보다 수용의도에 대한 설명력이 높다고 검증된 통합기술수용이론(UTAUT)을 적용하여 챗봇의 사용자 수용행동에 관한 모델을 구축하였다. 구체적으로, 수용의도의 결정요인인 성과기대, 예상노력, 사회적영향, 촉진조건이 수용의도에 긍정적인 영향을 미칠 것으로 예상하였다. 이 과정에서 수용의도 결정요인과 수용의도 간의 관계를 성별, 연령, 개인혁신성이 조절할 것으로 보았다. 본 연구는 챗봇의 수용에 영향을 미치는 결정요인과 조절변인의 효과를 검증하여 실무적 시사점을 제공하고자 한다.

• The Journal of the Korea Contents Association
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• v.9 no.12
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• pp.39-51
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• 2009

This study matters the design and implementation of an intelligent information search engine that is based on the $R^2SS$(Reverse Really Simple Syndication). Apart from to the previous method, where the user inputs the RSS address that one intends and obtains limited RSS information, the user just types in the information that one appoints to acquire the RSS information of standard documents that the user is interested among several RSS addresses by a Reverse RSS(Really Simple Syndication) method, which is drawn by the automated RSS address collection server in realtime. Through the proposed $R^2SS$(Really Reverse Simple Syndication) based intelligent information search engine, time can be significantly saved along with obtaining information with good quality, furthermore, it has the effects of having a personal secretary.

• Proceedings of the Korean Society of Computer Information Conference
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• 2017.01a
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• pp.147-150
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• 2017

지능형 로봇의 사용자 품질을 결정하는 주요 요소들 중 하나는 짧은 부트 시간이다. 로봇 시스템에서는 부팅 과정 중에 침입자인지, 자택 순찰, 개인 비서, 엔터테인먼트와 같은 다수의 응용들이 동시에 초기화되는데, 고품질의 사용자 경험을 제공하기 위해서는 사용자 응답성이 중요한 응용들이 우선적으로 초기화되어야한다. 이를 위해 리눅스 기반 로봇 시스템에서 부트 시간을 단축하기 위한 다양한 연구들이 진행되어 왔다. 하지만 이들은 단일 응용 각각에 대한 초기화 시간을 단축하는 연구들이며, 응용들 간에 CPU, 메모리, I/O와 같은 자원 경쟁에 의한 지연 요소를 고려하지 않고 있다. 본 논문에서는 응용들 간의 각종 자원경쟁들을 고려하여 사용자 응답성이 중요한 응용을 우선적으로 초기화하기 위한 외부 컨텍스트 기반 선별적 자원 사용률 조정기법을 제안한다. 이를 리눅스 기반 시스템 상에 구현하여 검증한 결과 응용의 부트 시간이 기존 대비 33.02% 단축됨을 확인했다.

• Journal of the Korean Institute of Intelligent Systems
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• v.14 no.6
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• pp.720-725
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• 2004

Robot systems have applied to manufacturing or industrial field for reducing the need for human presence in dangerous and/or repetitive tasks. However, robot applications are transformed from industrial field to human life in recent tendency Nowadays, final goal of robot is to make a intelligent robot that can understand what human say and learn by itself and have internal emotion. For example Home service robots are able to provice functions such as security, housework, entertainment, education and secretary To provide various functions, home robots need to recognize human`s requirement and environment, and it is indispensable to use artificial intelligence technology for implementation of home robots. In this paper, implemented robot system takes data from several sensors and fuses the data to recognize environment information. Also, it can select a proper behavior for environment using soft computing method. Each behavior is composed with intuitive motion and sound in order to let human realize robot behavior well.