2 research outputs found

    λͺ¨λ°”일 챗봇 μΈν„°νŽ˜μ΄μŠ€ 뢄석과 λ””μžμΈ μ œμ•ˆ

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    ν•™μœ„λ…Όλ¬Έ (석사)-- μ„œμšΈλŒ€ν•™κ΅ λŒ€ν•™μ› : 인지과학전곡, 2017. 2. μ΄μ€€ν™˜.μ „ μ„Έκ³„μ μœΌλ‘œ λͺ¨λ°”일 λ©”μ‹ μ €(mobile instant messenger) μ‚¬μš©μ΄ λŠ˜μ–΄λ‚˜λ©΄μ„œ λ©”μ‹ μ € μƒμ—μ„œ 인곡지λŠ₯(artificial intelligence)을 기반으둜 μ‚¬λžŒκ³Ό μžλ™μœΌλ‘œ λŒ€ν™”λ₯Ό λ‚˜λˆ„λŠ” μ‹œμŠ€ν…œμΈ 챗봇(chatbot)이 μ£Όλͺ© λ°›κ³  μžˆλ‹€. 이 μ—°κ΅¬λŠ” λͺ¨λ°”일 λ©”μ‹ μ € μƒμ—μ„œ λ™μž‘ν•˜λŠ” 챗봇 μΈν„°νŽ˜μ΄μŠ€ 뢄석을 μˆ˜ν–‰ν•˜μ˜€λ‹€. λ³Έ μ—°κ΅¬μ—μ„œλŠ” 챗봇 μ‚¬μš©μž μΈ‘λ©΄μ—μ„œ μ€‘μš”ν•œ μΈν„°νŽ˜μ΄μŠ€ μš”μ†Œμ— μ£Όλͺ©ν•˜μ—¬, 챗봇 μΈν„°νŽ˜μ΄μŠ€μ— λŒ€ν•œ μ‚¬μš©μžλ“€μ˜ κΈ°λŒ€μ™€ μš”κ΅¬μ‚¬ν•­μ„ μ •λ¦¬ν•˜κ³  챗봇 μΈν„°νŽ˜μ΄μŠ€ λ””μžμΈ λ°©ν–₯을 μ œμ•ˆν•˜κ³ μž ν•˜μ˜€λ‹€. λ¨Όμ € μ‚¬μš©μžλ“€μ΄ 챗봇과 λŒ€ν™”λ₯Ό μ§„ν–‰ν•˜λ©° νŠΉμ • λͺ©μ μ„ μˆ˜ν–‰ν•˜λŠ” κ³Όμ •μ—μ„œ ν•„μš”ν•œ μΈν„°νŽ˜μ΄μŠ€ μš”μ†Œκ°€ 무엇인지 μ•Œμ•„λ³΄κΈ° μœ„ν•˜μ—¬ λ‹€μ–‘ν•œ 챗봇 μ„œλΉ„μŠ€λ₯Ό λŒ€μƒμœΌλ‘œ μ‚¬μš©μž 행동을 κ΄€μ°°ν•˜κ³  λΆ„μ„ν•˜λŠ” μ»¨ν…μŠ€μΆ”μ–Ό 인콰이어리(contextual inquiry) 쑰사λ₯Ό μ‹€μ‹œν•˜μ˜€λ‹€. κΈ°μ‘΄ 연ꡬ와 μ‚¬μš©μž 쑰사λ₯Ό 톡해 μˆ˜μ§‘λœ 데이터λ₯Ό λ°”νƒ•μœΌλ‘œ μ±—λ΄‡μ—μ„œ μ‚¬μš©μžκ°€ νƒœμŠ€ν¬λ₯Ό μˆ˜ν–‰ν•˜λŠ”λ° ν•„μš”ν•œ μΈν„°νŽ˜μ΄μŠ€ μš”μ†Œμ™€ 각각에 λŒ€ν•œ μš”κ΅¬μ‚¬ν•­μ„ μ •λ¦¬ν•˜μ˜€λ‹€. μˆ˜μ§‘λœ μ‚¬μš©μž 쑰사 데이터λ₯Ό λΆ„μ„ν•˜μ—¬ 챗봇 μΈν„°νŽ˜μ΄μŠ€μ—μ„œ μ‚¬λžŒλ“€μ΄ μ€‘μš”ν•˜κ²Œ μƒκ°ν•˜λŠ” 지점을 μ°ΎκΈ° μœ„ν•΄, μ›μžλ£Œλ₯Ό λΆ„ν•΄ν•˜κ³  μ—¬λŸ¬ κ°œλ…λ“€μ„ λ„μΆœν•œ ν›„, κ΄€λ ¨ μžˆλŠ” κ°œλ…λ“€μ„ λ¬Άμ–΄ μƒμœ„ 주제λ₯Ό λ„μΆœν•˜λŠ” λ°©μ‹μ˜ κ·Όκ±° 이둠 μ ‘κ·Ό 방법(grounded theory approach)이 μ‚¬μš©λ˜μ—ˆλ‹€. μš°μ„ , μ‚¬μš©μžλ“€μ€ μ±—λ΄‡μ˜ 지λŠ₯적 역할을 κΈ°λŒ€ν•˜κ³  μžˆμ—ˆμœΌλ©°, 챗봇 μž‘λ™ λ°©μ‹μ˜ μ˜ˆμΈ‘κ°€λŠ₯μ„±, λ‹¨μˆœμ„±, 직관성, μΉœμˆ™μ„±, 일관성을 μ€‘μš”μ‹œν•˜λŠ” κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. λ˜ν•œ μ‚¬λžŒ κ°„μ˜ μ˜μ‚¬μ†Œν†΅ 방식을 κΈ°μ€€μœΌλ‘œ μ±—λ΄‡κ³Όμ˜ μ˜μ‚¬μ†Œν†΅μ„ ν‰κ°€ν•˜λ©°, 정확성이 지속적인 μ‚¬μš©μ„ μœ λ„ν•˜λŠ”λ° μ€‘μš”ν•œ κ²ƒμœΌλ‘œ λ°ν˜€μ‘Œλ‹€. 챗봇 μΈν„°νŽ˜μ΄μŠ€ λ””μžμΈμ— μžˆμ–΄μ„œλŠ” μš°μ„  μ±—λ΄‡μ˜ 지λŠ₯적 츑면을 λ“œλŸ¬λ‚΄λŠ” 것이 μ€‘μš”ν•œ κ²ƒμœΌλ‘œ λ‚˜νƒ€λ‚¬λ‹€. 그뿐만 μ•„λ‹ˆλΌ, 이λͺ¨ν‹°μ½˜, λ―Έλ””μ–΄ λ“±μ˜ μš”μ†Œλ₯Ό 톡해 μ±—λ΄‡μ˜ μ‚¬νšŒμ  지λŠ₯을 μ „λ‹¬ν•˜λŠ” 것도 μ€‘μš”ν•œ κ²ƒμœΌλ‘œ λ“œλŸ¬λ‚¬λ‹€. μ‚¬μš©μžμ™€μ˜ μ›ν™œν•œ λŒ€ν™” 진행을 μœ„ν•΄ 챗봇 ν”„λ‘œν•„, λΉ λ₯Έ 응닡 λ“±μ˜ μš”μ†Œλ₯Ό 톡해 μ±—λ΄‡μ˜ μ—­λŸ‰μ„ 전달할 ν•„μš”μ„±λ„ μ‚΄νŽ΄λ³Ό 수 μžˆμ—ˆλ‹€. 이 μ—°κ΅¬λŠ” μ±—λ΄‡μ—μ„œ λͺ¨λ°”일 μΈν„°νŽ˜μ΄μŠ€κ°€ μ£Όμš”ν•  역할을 μˆ˜ν–‰ν•œλ‹€λŠ” 점에 μ΄ˆμ μ„ λ§žμΆ”μ–΄ 챗봇 μΈν„°νŽ˜μ΄μŠ€μ— λŒ€ν•œ 연ꡬλ₯Ό μ§„ν–‰ν–ˆλ‹€λŠ” μ μ—μ„œ 기쑴의 μŒμ„± μ–Έμ–΄ 기반의 λŒ€ν™”ν˜• μ‹œμŠ€ν…œ 연ꡬ듀과 차별점을 μ§€λ‹Œλ‹€. λ˜ν•œ 이 μ—°κ΅¬λŠ” μ‚¬μš©μž μΈ‘λ©΄μ—μ„œ 챗봇 μΈν„°νŽ˜μ΄μŠ€μ˜ μ€‘μš” 지점을 μ •λ¦¬ν•˜κ³  ν•„μš”ν•œ μΈν„°νŽ˜μ΄μŠ€ λ””μžμΈ λ°©ν–₯을 μ œμ•ˆν•˜μ—¬ 챗봇 μΈν„°νŽ˜μ΄μŠ€μ— λŒ€ν•œ 심측적인 이해λ₯Ό 도λͺ¨ν•˜μ˜€λ‹€.β… . 연ꡬ배경 1 β…‘. κ΄€λ ¨ 연ꡬ 및 연ꡬ 문제 4 1. λŒ€ν™”ν˜• μ—μ΄μ „νŠΈμ™€ 챗봇 4 2. μΈν„°νŽ˜μ΄μŠ€ 7 3. μ—°κ΅¬λ¬Έμ œ 9 β…’. 챗봇 μ‚¬μš©μž 쑰사 11 1. μ‚¬μš©μž 쑰사 방법 11 2. μ‚¬μš©μž 쑰사 λ‚΄μš© 21 β…£. μ‚¬μš©μž 쑰사 κ²°κ³Ό 39 1. μ‚¬μš©μž 쑰사 κ²°κ³Ό 뢄석 방법 39 2. μ‚¬μš©μž 쑰사 κ²°κ³Ό 39 3. 챗봇 μΈν„°νŽ˜μ΄μŠ€ λ””μžμΈ μ œμ•ˆ 44 β…€. λ…Όμ˜ 48 β…₯. κ²°λ‘  50 β…¦. μ°Έκ³ λ¬Έν—Œ 52 ABSTRACT 57Maste

    A culturicon design model for communication across culture

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    Emoticons are important in Computer-Mediated Communication due to its capability to express emotions/actions without face-to-face meeting. However, existing emoticons are still incompatible and lack some human expressions that limit user’s selection, particularly in terms of culture. Based on the comprehensive literature review conducted, the study regarding emoticons in cultural perspective is limited and there are demand for more cultural-based emoticons to be developed. To solve the issue, this study developed a model named Culturicon Design Model (CDM) by incorporating appropriate cultural dimensions and icon design principles, where Culturicon is the combination of β€˜culture’ and β€˜icon’. The components of CDM were determined based on previous study’s findings. CDM was then verified through expert review by applying a convergent parallel mixed method that measured the model’s components, flow, and readability, involving 11 experts. Then, CDM was validated by applying an explanatory sequential mixed method involving two phases – validation by designers and validation by end users. Validation by designers measured the components of the model in terms of gain satisfaction, interface satisfaction, task support satisfaction, and emoticon samples’ development, involving five designers. The validation by the end user was performed through focus group discussions, involving eight participants. Thematic analysis was used to analyse focus group’s results. The final version of CDM comprises five cultural dimensions (high power distance, high collectivism, low uncertainty avoidance, moderate masculinity/femininity, and long-term relationships), and eight Human Computer Interaction (HCI) icon design principles (familiar, understandable, attractive, coherent, informative, distinct, memorable, and legible). Focus group’s result showed that the emoticon’s samples represent the cultural elements, fulfilled the HCI icon design principles, and useful in their communication across culture. CDM contributed to the body of knowledge in HCI. It can be a guideline for designers to develop Culturicon in the future, hence providing more emoticon selections from local culture to satisfy end user’s needs
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