• Annual Conference of KIPS
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• 2013.05a
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• pp.1067-1069
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• 2013

전자상거래 시장의 급격한 성장에 따라 고객이 원하는 정보를 얻기 위해 소요되는 시간과 노력을 절약하기 위한 방안으로 추천 시스템의 필요성이 강조되고 있다. 추천 시스템에 일반적으로 가장 많이 쓰이는 것이 협업필터링 기법이다. 협업 필터링은 추천시스템 분야에서 가장 성공적인 기법으로 전자상거래 포털에서 가장 널리 이용되고 있다. 그러나 희박성, 확장성, 투명성 등의 문제점을 가진다. 본 논문에서는 프로파일링 기법을 사용해 협업필터링의 희박성 문제 해소 방안으로 개인성향을 이용하여, 보다 정확한 추천을 하여 온라인 서점에 적용할 수 있는 추천 시스템이다.

• Annual Conference of KIPS
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• 2009.04a
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• pp.242-245
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• 2009

현재 대형 디스플레이는 여러 공공장소에 설치되어 장소의 목적에 맞는 정보를 제공한다. 이러한 대형 디스플레이는 가까운 미래에 더욱 많은 장소에 비치되어 사용될 것으로 기대된다. 또한 사용자와의 인터랙션을 통해 개인화된 정보를 제공하거나 원격지에 위치한 디스플레이 간의 상호작용도 가능할 것으로 보인다. 최근 대형 디스플레이로 고해상도의 타일드 디스플레이가 관심을 끌고 있다. 그러나 타일드 디스플레이는 분산 환경 시스템을 사용하므로 소프트웨어 개발의 복잡도가 높다. 본 논문에서는 분산환경의 타일드 디스플레이의 응용프로그램과 타일드 디스플레이들 간의 사용자 인터랙션을 통한 협업을 지원하는 확장된 iTILE 프레임워크를 살펴보고, 시스템 구조와 실험결과를 분석한다.

• Annual Conference of KIPS
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• 2009.11a
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• pp.785-786
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• 2009

인터넷의 수많은 정보 속에서 사용자가 원하는 적절한 정보를 찾아 주기 위해 추천 시스템이 등장하였다. 기존의 추천 시스템들은 유사한 선호도를 갖는 사람들을 그룹화 하여 그들이 선호할 만한 아이템을 추천해 주는 방법을 사용하는데, 본 논문에서는 기존의 추천 시스템에 태그를 이용하여 추천의 신뢰도를 높이고자 한다. 사용자가 해당 아이템을 보고난 후 추가로 더 알고 싶은 내용에 대한 태그를 등록하면 그 태그는 다른 사용자들을 위한 추천 정보로 이용된다. 또한 추천 자료에 대한 사용자의 만족도 평가를 바탕으로 자료간의 연관 관계를 재조정하여 추천 시스템의 성능을 높인다.

• Smart Structures and Systems
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• v.26 no.1
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• pp.11-21
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• 2020

The hinge joint is the key to the overall cooperative working performance of the assembled beam bridge, and it is also the weakest part during the service period. This paper proposes a method for monitoring and evaluating the lateral cooperative working performance of fabricated beam bridges based on dynamic strain correlation coefficient indicator. This method is suitable for monitoring and evaluation of hinge joints status between prefabricated girders and overall cooperative working performance of bridge, without interruption of traffic and easy implementation. The remote cloud monitoring and diagnosis system was designed and implemented on a real assembled beam bridge. The algorithms of data preprocessing, online indicator extraction and status diagnosis were given, and the corresponding software platform and scientific computing environment for cloud operation were developed. Through the analysis of real bridge monitoring data, the effectiveness and accuracy of the method are proved and it can be used in the health monitoring system of such bridges.

• Journal of Distribution Science
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• v.18 no.12
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• pp.45-54
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• 2020

Purpose: Indonesia's maritime logistics and distribution system is currently faced with several challenges, some of which include prolonged export and import time for goods handling as well as the high logistics cost. This study further analyzes the existing business processes in maritime logistics in East Java Province in order to provide solutions to the challenges. Research design, data and methodology: This research was carried out in East Java Province, Indonesia, with data collected through field observations, documentation, and in-depth interviews with all the stakeholders involved. Results: The study showed that the number of stakeholders and activities involved in the flow of goods movement ultimately impacted the length of time. These factors can be classified into the following five: 1) export and import regulations, 2) third party logistics competencies, 3) transportation infrastructure and facilities, 4) adoption of information systems and technology, and 5) maritime line connectivity. Conclusion: Analyzing the three supply chain flows in the maritime logistics and distribution industry called for the need for improvement to increase coordination among related institutions, improve the flexibility of dwelling time to the conditions of each port, enhance service levels, improve transportation infrastructure and facilities, implement information system and technology, and develop shipping routes and networks. Therefore, a collaborative supply chain management system can be realized.

• Asia pacific journal of information systems
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• v.29 no.4
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• pp.752-770
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• 2019

The purpose of this study is to incorporate telemarketing processes to improve telemarketing performance. For this application, we have attempted to mix the model of machine learning to extract potential customers with personalisation techniques to derive recommended products from actual contact. Most of traditional recommendation systems were mainly in ways such as collaborative filtering, which predicts items with a high likelihood of future purchase, based on existing purchase transactions or preferences for products. But, under these systems, new users or items added to the system do not have sufficient information, and generally cause problems such as a cold start that can not obtain satisfactory recommendation items. Also, indiscriminate telemarketing attempts can backfire as they increase the dissatisfaction and fatigue of customers who do not want to be contacted. To this purpose, this study presented a multi-purpose hybrid recommendation algorithm to achieve two goals: to select customers with high possibility of contact, and to recommend products to selected customers. In addition, we used subscription data from telemarketing agency that handles insurance products to derive realistic applicability of the proposed recommendation system. Our proposed recommendation system would certainly solve the cold start and scarcity problem of existing recommendation algorithm by using contents information such as customer master information and telemarketing history. Also. the model could show excellent performance not only in terms of overall performance but also in terms of the recommendation success rate of the unpopular product.

• Proceedings of the Korean Information Science Society Conference
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• 2007.10d
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• pp.589-592
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• 2007

CoSlide 협업 시스템은 웹데브 기반의 CoSlide 서버와 윈도우즈 응용프로그램인 CoSpace 클라이언트로 구성된다. CoSlide 서버는 Jakarta Slide 서버의 확장으로 협업시스템 구성원간의 자원 공유를 위한 다양한 종류의 작업장을 지원하며, CoSpace 클라이언트는 CoSlide 서버의 다양한 기술 지원을 사용자 중심의 인터페이스로 제공한다. 협업을 동적으로 지원하기 위해서는 워크플로우 시스템이 필요하다. 워크플로우 시스템은 협업시스템에 등록된 사용자가 워크플로우가 정의된 작업장에 자원을 등록하였을 때 정의된 워크플로우에 따라서 자원의 이동, 복사 그리고 메시지전송 등의 과정을 자동적으로 수행한다. 워크플로우 정의는 XML 파일 형식으로 워크플로우 작업장에 생성되어 존재하며 반응적 워크플로우가 발생하였을 때 XML 파일의 정의에 따라 자동적으로 이뤄진다. 협업 시스템에 워크플로우 시스템을 적용시키면 협업 시스템에 등록된 자원을 수동으로 분류하거나 협업에 필요한 다른 그룹의 특정 사용자에게 수동으로 전송해야 하는 불편함을 없앨 수 있다.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.17 no.4
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• pp.1200-1215
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• 2023

With the development of IoT and artificial intelligence, location-based services are getting more and more attention. For solving the current problem that indoor positioning error is large and generalization is poor, this paper proposes a Model Stacking Algorithm for Indoor Positioning System using WiFi fingerprinting. Firstly, we adopt a model stacking method based on Bayesian optimization to predict the location of indoor targets to improve indoor localization accuracy and model generalization. Secondly, Taking the predicted position based on model stacking as the observation value of particle filter, collaborative particle filter localization based on model stacking algorithm is realized. The experimental results show that the algorithm can control the position error within 2m, which is superior to KNN, GBDT, Xgboost, LightGBM, RF. The location accuracy of the fusion particle filter algorithm is improved by 31%, and the predicted trajectory is close to the real trajectory. The algorithm can also adapt to the application scenarios with fewer wireless access points.

• Journal of Broadcast Engineering
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• v.14 no.2
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• pp.238-252
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• 2009

Due to the rapid increase of available contents via the convergence of broadcasting and internet, the efficient access to personally preferred contents has become an important issue. In this paper, for recommendation scheme for TV programs using a collaborative filtering technique is studied. For recommendation of user preferred TV programs, our proposed recommendation scheme consists of offline and online computation. About offline computation, we propose reasoning implicitly each user's preference in TV programs in terms of program contents, genres and channels, and propose clustering users based on each user's preferences in terms of genres and channels by dynamic fuzzy clustering method. After an active user logs in, to recommend TV programs to the user with high accuracy, the online computation includes pulling similar users to an active user by similarity measure based on the standard preference list of active user and filtering-out of the watched TV programs of the similar users, which do not exist in EPG and ranking of the remaining TV programs by proposed rank model. Especially, in this paper, the BM (Best Match) algorithm is extended to make the recommended TV programs be ranked by taking into account user's preferences. The experimental results show that the proposed scheme with the extended BM model yields 62.1% of prediction accuracy in top five recommendations for the TV watching history of 2,441 people.

• Journal of Broadcast Engineering
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• v.18 no.6
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• pp.816-822
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• 2013

The latest video coding standard HEVC was developed by the joint work of JCT-VC(Joint Collaborative Team on Video Coding) from ITU-T VCEG and ISO/IEC MPEG. The HEVC standard reduces the BD-Bitrate of about 50% compared with the H.264/AVC standard. However, using the various methods for obtaining the coding gains has increased complexity problems. The proposed method reduces the complexity of HEVC by using both CPU parallel processing and GPU-accelerated processing. The experiment result for UHD($3840{\times}2144$) video sequences achieves 15fps encoding/decoding performance by applying the proposed method. Sooner or later, we expect that the H/W speedup of data transfer rates between CPU and GPU will result in reducing the encoding/decoding times much more.