• Proceedings of the Korean Information Science Society Conference
• /
• 2008.06c
• /
• pp.522-526
• /
• 2008

모션 캡쳐 장비는 사람의 자연스러운 행동이나 동작 정보를 정밀하게 얻기 위해 널리 사용되며, 영화나 게임과 같은 콘텐츠에서 자주 활용되고 있다. 하지만 모션 캡쳐 장비가 고가이기 때문에 한번 입력받은 데이터를 모션별로 분할하고 상황에 맞게 재결합하여 사용할 필요가 있으며, 입력 데이터를 모션별로 분할하는 것은 대부분 수동으로 이루어진다. 이 때문에 캡쳐된 데이터를 자동으로 분할하기 위한 연구들이 다양하게 시도되고 있다. 기존의 연구들은 크게 전역적 특성에 대한 고려없이 이웃하는 프레임만을 고려하는 온라인 방식과 데이터를 전역적으로 고려하나 이웃하는 프레임 사이의 관계를 고려하지 않는 오프라인 방식으로 나누어진다. 본 논문에서는 온라인과 오프라인 방식을 병합한 그래프 기반의 모션 분할 방법을 제안한다. 분할을 위해 먼저 모션데이터를 기반으로 그래프를 생성하며, 그래프는 이웃하는 각 프레임사이의 유사도뿐만 아니라 시간축을 기반으로 일정시간내의 프레임들의 유사도를 모두 고려하였다. 이렇게 생성된 그래프를 분할하기 위해 분할된 모션내의 유사도 합을 최소화하고 각 모션간의 유사도는 최대화할 수 있는 normalized cuts을 이용하였다. 실험에서 제안된 방법은 기존의 오프라인 방식 중 하나인 GMM과 온라인 방식 중 하나인 국부최소값 분할 방법보다 좋은 결과를 보였으며, 이는 각 프레임 사이의 유사도뿐만 아니라 일정시간내의 유사도를 전역적으로 고려하기 때문이다.

• The Journal of Society for e-Business Studies
• /
• v.19 no.3
• /
• pp.65-89
• /
• 2014

Although many studies have focused on the influences and outcomes of personal information leakage, few studies have investigated how the personal information leakage prevention behavior differs depending on internet user. This study attempts to supplement the existing studies' limitations with the use of risk perception attitude (RPA) framework. More specifically, this study tries to show internet user can be classified into four groups based on perceived risk of personal information leakage and efficacy beliefs of personal information protection, and to identify how the groups differ in terms of motivation, information seeking, and behaviors for privacy leakage prevention. Analysis on survey data from 276 internet users reveals that the users can be classified into responsive, avoidance, proactive, indifference groups. Furthermore, there are differences between groups in terms of motivation, information seeking, and behaviors for personal information leakage prevention. This study contributes to expand existing literature by providing tailored guidelines for implementation of personal information protection strategies and policy.

• Information Systems Review
• /
• v.26 no.1
• /
• pp.119-149
• /
• 2024

This study investigates the antecedents and mechanisms influencing trust and behavioral intentions formation towards new AI chatbots, such as ChatGPT, as travel information searching services. Analyzing the roles of variables such as familiarity, novelty, personal innovativeness, information quality and perceived anthropomorphism, the research elucidates the impact of these factors on users' cognitive and affective trust, ultimately affecting their intention to adopt information and sustain the use of the AI chatbot. Results indicate that perceived familiarity and information quality positively influence both cognitive and affective trust, whereas perceived novelty contributes positively only to cognitive trust. Additionally, the personal innovativeness of new AI chatbot users was found to weaken the effect of familiarity on perceived trust, while the perceived level of anthropomorphism of the chatbot amplified the effects of novelty and familiarity on cognitive trust. These findings underscore the importance of considering factors such as familiarity, personal innovativeness, information quality and anthropomorphism in the design and implementation of AI chatbots, affecting trust and behavioral intention.

• Journal of Intelligence and Information Systems
• /
• v.26 no.1
• /
• pp.151-166
• /
• 2020

A recommender system is a system that recommends products or services that best meet the preferences of each customer using statistical or machine learning techniques. Collaborative filtering (CF) is the most commonly used algorithm for implementing recommender systems. However, in most cases, it only uses purchase history or customer ratings, even though customers provide numerous other data that are available. E-commerce customers frequently use a search function to find the products in which they are interested among the vast array of products offered. Such search keyword data may be a very useful information source for modeling customer preferences. However, it is rarely used as a source of information for recommendation systems. In this paper, we propose a novel hybrid CF model based on the Doc2Vec algorithm using search keywords and purchase history data of online shopping mall customers. To validate the applicability of the proposed model, we empirically tested its performance using real-world online shopping mall data from Korea. As the number of recommended products increases, the recommendation performance of the proposed CF (or, hybrid CF based on the customer's search keywords) is improved. On the other hand, the performance of a conventional CF gradually decreased as the number of recommended products increased. As a result, we found that using search keyword data effectively represents customer preferences and might contribute to an improvement in conventional CF recommender systems.

• Journal of Internet Computing and Services
• /
• v.3 no.1
• /
• pp.11-16
• /
• 2002

Nowday, Cyber shopping mall increased market size. The Consumer Behavior chainged new trend. This study on the systematic access to establishment of the concept of cyber shopping mall as well as to problems to overall parts of EC service as well is required. The objectives of this study are that how service consumers perceive the quality of EC service, and that what effect the quality makes on their satisfaction and re-purchase intention. This means that the research enables a marketing manager to take the meaning of comparative weight among the components of EC service quality, and to provide very useful information to establish marketing strategies which are close to the consumers.

• Journal of the Korea Computer Industry Society
• /
• v.2 no.7
• /
• pp.945-952
• /
• 2001

In consequence of expansion of internet users, electronic commerce is becoming a new prototype for marketing and sales, arid most of electronic commerce sites or internet shopping malls provide a rich source of information and convenient user interfaces about the organizations customers to maintain their patrons. One of the convenient interfaces for users is service to recommend products. To do this, they must exploit methods to extract and analysis specific patterns from purchasing information, behavior and market basket about customers. The methods are association rules and sequential patterns, which are widely used to extract correlation among products, and in most of on-line electronic commerce sites are executed with users information and purchased history by category-oriented. But these can't represent the diverse correlation among products and also hardly reflect users' buying patterns precisely, since the results are simple set of relations for single purchased pattern. In this paper, we propose an efficient mining technique, which allows for multiple purchased patterns that are category-independent and have relationship among items in the linked structure of single pattern items.

• The Journal of the Korea Contents Association
• /
• v.5 no.3
• /
• pp.19-28
• /
• 2005

It is true that internet provides consumers with an efficient way to search information with minimal effort and cost, which facilitates better decision making. Especially, previous studies revealed that the online word-of-mouth marketing is widely used as a source of consumers' information seeking and purchase decision making. Even with this importance of the online word-of-mouth communication on internet few researches have systematically addressed the issue. This study investigates the effect of consumers' motives on perceived usefulness of word-of-mouth marketing in online shopping mall contents. The results are as follows: First, choice uncertainty, perceived sacrifice, and social pressure play an important role for perceived usefulness of word-of-mouth marketing. Second, perceived usefulness has directly affected consumers' quality perception. Thus, it is essential for internet companies to find ways to encourage their customers to engage in word-of-mouth communication on their websites.

• Proceedings of the Korea Inteligent Information System Society Conference
• /
• 2002.11a
• /
• pp.215-219
• /
• 2002

인터넷의 급속한 성장으로 e비즈니스의 인터넷 사용이 증대되었다. 인터넷 환경에서는 새로운 인터넷 사용자라는 소비자를 대상으로 인터넷 소비자 행동에 관한 연구가 중요한 분야로 자리잡게 되었다. 인터넷상에서의 소비자 행동을 설명하기 위해 온라인 인지절차 (Cognitive process)에 관한 연구로, 웹 사이트에 대한 소비자의 태도에 미치는 영향을 밝히는 연구들이 수행되었다. 웹 사이트에 대한 소비자의 태도에 따른 개인화된 마케팅을 위해서는 웹사이트를 소비자의 특성을 고려해서 개인화된 웹사이트를 운영해야 한다. 개인의 정보 시스템 사용에 대한 설명을 위하여 많은 모형들이 개발되어 왔다. 기술 수용 모형(Technology Acceptance Model: TAM)은 개인의 정보 시스템 수용에 영향을 미치는 요소를 설명하기 위하여 가장 폭 넓게 사용되고 있는 모형이다. TRA 모형에 따르면, 개인의 사회적 행위는 그 행위의 결과에 대한 신념에 의해 영향을 받는다고 할 수 있다. 본 연구에서는 고객의 신념을 신뢰 (Trust), 유용성 (Usefulness), 사용의 편의성 (Ease of Use), 위험 (Risk), 보안통제 (Security control)로 분류하고, 고객의 실제 사용 (Usage)을 인터넷 뱅킹 환경에서 측정하여 고객세분화에 적용하였다. 세분화된 고객집단을 분류하기 위해서 인공신경망, 판별 분석 기법을 적용하여 웹 사이트에서 사용할 수 있는 개인화 모형을 개발하였다.

• Journal of Digital Convergence
• /
• v.10 no.4
• /
• pp.279-286
• /
• 2012

The purpose of this study was identified the influence of introducing Electronic Medical Records (EMR) on reception attitude, based on literature investigation, the study converted utility and serviceability from Davis TAM Model into awareness of effects in computerized database except attitude variable. The electronic survey for doctors, nurses, medical technicians of a general hospital located in Gangwon-do was performed for 4 weeks from Nov, 11th, 2009 to Dec, 2nd and the collected data was computerized through SPSS 12.0. The factors influencing reception attitude were divided into 4 categories; basic characteristics of the individual, awareness of privacy protection, awareness of effects in computerized database, technological preparation and measured detailed specific variables. As the result of this, the factors influencing reception intention were different depending on recognizing the effectiveness caused by computerization of medical information. Especially, in terms of the difference between basic characteristics of the individual and awareness of privacy protection, there were significant distinctions among 3 sectors; general, transactional, online information management. The significant effects were identified from information management related to business or online information management depending on experiencing security education.

• Journal of the Korean Society for information Management
• /
• v.37 no.3
• /
• pp.275-299
• /
• 2020

This study investigates the factors affecting behavioral intention of professors and students at universities to use academic libraries in a hybrid library environment where a traditional physical library is combined with a digital library that is centered on online information use. The structural relationships among factors were also analyzed in this study by utilizing a combined behavioural model which was based on TPB and TAM. This study identified users' intention to use academic libraries according to changes in the use environment, and the findings of this study bring a valuable meaning to library administrators for setting up the strategic plan for the future of academic libraries. The results of this study imply that academic libraries should strategically setup an effective and efficient operating plan based on awareness, attention and cooperation, in order to survive as well as to accomplish balanced growth in rapidly changing environment.