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홍태호(Tae-ho Hong),서기열(Ki-yeol Seo),박계각(Gyei-Kark Park) 한국지능시스템학회 2005 한국지능시스템학회 학술발표 논문집 Vol.15 No.1
현재 선박에서 항해사에게 항로정보를 제공하는 장비는 ECDIS와 GPS 플로터가 많이 사용되고 있으나 자동항로생성 및 항로설명기능이 없어 숙련된 항해사만 사용할 수 있는 문제가 있으며, 특히 종이해도의 대체 시스템인 ECDIS에 사용되는 ENC를 이용한 자동항로생성 및 항로 설명에 관한 연구는 없는 실정이다. ENC는 IHO에서 정의한 S-52, S-57 표준포멧을 기반으로 제작된다. 본 논문에서는 ENC의 해도데이터와 GPS의 위치데이터, Anemometer의 풍향ㆍ풍속데이터, 조류데이터를 이용하여 현 위치에서 목적지까지의 최적항로를 설계하여 안내해주는 통합형 항해가이딩시스템(INGS)을 구축하여 그 유효성을 확인하였다.
홍태호(Tae-ho Hong),이정구(Jeong-koo Lee),김은미(Eun-mi Kim) 한국인터넷전자상거래학회 2009 인터넷전자상거래연구 Vol.9 No.3
Online stores have grown dramatically under the influence of the rapid expansion of the Internet use and the information technology development. The online market doesn’t give any attractive advantage more after first movers of Internet stores have grown as large enterprises in all industry sectors. The Internet shopping malls have faced to a fierce competition with their competitors on Internet because of customer’s high mobility from one store to others. The retention of customers is the most important issue for online merchandiser and a lot of studies have focused on online customer’s intention to purchase. Therefore, this study presented a model for explaining the impacts of Internet shopping mall’s quality on customer’s intention to purchase. We built the research model by integrating the element of Internet shopping mall with customer’s trust on the shopping malls. The empirical analyses are presented through structural equation model with collected data from a survey of 205 customers. Data analyses show that the trust and quality of the website affects perceived ease of use and usefulness of Internet shopping malls, and also those perceived ease of use and usefulness affects the intention to purchase on the Internet shopping malls.
소셜 네트워크 사이트의 사용자 충성도에 관계혜택과 사회적 영향이 미치는 영향
홍태호 ( Tae Ho Hong ),옥석재 ( Seok Jae Ok ),박인경 ( In Gyong Park ),김은미 ( Eun Mi Kim ) 한국지식경영학회 2013 지식경영연구 Vol.14 No.1
Due to the development of social networks and smartphones, many different kinds of issues have emerged in business and society. By reflecting these trends, social network sites have appeared and they are recognized as the new concept of sites. The major feature of the social network sites is that the social relationship had been taken to the online space. Social network sites support the formation of a network and offer users the relationship between users offline as well as on the features mentioned above, users enjoy the benefits using social network sites. These social network sites in the enterprise can be used to form relationships with customers. This study identified the influencing factors as relational benefits and social influence on relationship commitment in social network sites. In addition, we analyzed that how the relationship commitment between users affects user loyalty after their using social network sites. We presented empirical results by utilizing structural equation model with 244 respondents and the significant implications for the academy and the practice with discussions.
LDA를 이용한 온라인 리뷰의 다중 토픽별 감성분석 - TripAdvisor 사례를 중심으로 -
홍태호 ( Hong Tae-ho ),니우한잉 ( Niu Hanying ),임강 ( Ren Gang ),박지영 ( Park Ji-young ) 한국정보시스템학회 2018 情報시스템硏究 Vol.27 No.1
Purpose There is much information in customer reviews, but finding key information in many texts is not easy. Business decision makers need a model to solve this problem. In this study we propose a multi-topic sentiment analysis approach using Latent Dirichlet Allocation (LDA) for user-generated contents (UGC). Design/methodology/approach In this paper, we collected a total of 104,039 hotel reviews in seven of the world's top tourist destinations from TripAdvisor (www.tripadvisor.com) and extracted 30 topics related to the hotel from all customer reviews using the LDA model. Six major dimensions (value, cleanliness, rooms, service, location, and sleep quality) were selected from the 30 extracted topics. To analyze data, we employed R language. Findings This study contributes to propose a lexicon-based sentiment analysis approach for the keywords-embedded sentences related to the six dimensions within a review. The performance of the proposed model was evaluated by comparing the sentiment analysis results of each topic with the real attribute ratings provided by the platform. The results show its outperformance, with a high ratio of accuracy and recall. Through our proposed model, it is expected to analyze the customers’ sentiments over different topics for those reviews with an absence of the detailed attribute ratings.
홍태호 ( Tae Ho Hong ),박지영 ( Lian Ying Pei ),배련영 ( Soo Hyung Choi ),최수형 ( Ji Young Park ) 한국정보시스템학회 2012 情報시스템硏究 Vol.21 No.2
In this paper, we identified the factors influencing on the continuous use intention of social commerce and analyzed the proposed model empirically using structural equation model, which was developed by considering hedonic and utilitarian shopping value, trust, satisfaction, familiarity, social influence, and perceived price. We collected data for this study by surveying the consumers who had an experience of purchasing through social commerce. An analysis of 212 respondents indicated that utilitarian and hedonic shopping value influenced on satisfaction as both of shopping value are significant statistically. Social commerce gives more attraction their consumers by reducing the price to half, whereas they are expected to present playfulness of shopping. Familiarity, social influence, and perceived price are influential factors in a purchase of social commerce sites. We discuss the implications of our findings for both theory and practice.
공통 팔로워 중복 집단에 기반한 인플루엔셜 랭킹 알고리즘을 이용한 마이크로블로그의 팔로위 추천
홍태호 ( Tae Ho Hong ),박지영 ( Ji Young Park ),이태원 ( Tae Won Lee ),장청롱 ( Cheng Long Zhang ) (주)엘지씨엔에스(구 LGCNS 엔트루정보기술연구소) 2013 Entrue Journal of Information Technology Vol.12 No.3
본 연구에서는 마이크로블로그의 팔로위 추천을 위해 공통 팔로워 중복 집단에 기반한 인플루엔셜 랭킹알고리즘을 이용한 추천모형을 개발하였다. 제안 알고리즘은 마이크로블로그의 팔로위를 추천할 때, 공통 팔로워의 중복 집단을 이용함으로써 계산시간을 대폭 줄이고 적중률 또한 기존의 방법론보다 높일 수 있었다. 제안 알고리즘을 이용하여 중국의 마이크로블로그인 텐센트 웨이보(Tencent Weibo)에 적용한 결과 팔로위 추천 정확도가 증가하였다. The objective of this paper is to provide recommender model to recommend the followees in microblog using influential ranking algorithm based common follower duplicate group. The proposed algorithm was able to recommend microblog`s fol-lowees with shorter processing time than the previous influential ranking algorithm. In addition, the hit ratio of the recom-mended followees gained from the proposed algorithm showed more improved performance when it was applied to Tencent Weibo, which is the most popular microblog in China.