• Journal of Digital Convergence
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• v.17 no.12
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• pp.235-241
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• 2019

The structure of the IoT can be divided into devices, gateways, and servers. First, the gateway collects data from the device, and the gateway sends data to the server through HTTP protocol, Websocket protocol, and MQTT protocol. The processing server then processes, analyzes, and transforms the data, and the database makes it easy to store and use this data. These IoT services are basically centralized structures with servers, so attacks on the entire platform are concentrated only on the central server, which makes hacking more successful than distributed structures. One way to solve this problem is to develop IoT that combines blockchain. Therefore, the proposed research suggests that the blockchain is a distributed structure, in which blocks containing small data are connected in a chain form, so that each node agrees and verifies the data with each other, thereby increasing reliability and lowering the probability of data forgery.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.811-814
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• 2011

This paper presents smart laundry management system using wireless Radio Frequnecy Identification (RFID) reader for efficient managing a large amount of laundry and clothing. The proposed system is comprised of wireless RFID hanger, base module connected on PC, and server system. The wireless RFID hanger with RFID reader read RFID tag attached on clothes and transmit tag information using wireless communication. The server system manage customers and his clothing using Database (DB) and display the information on the web page and smart phone devices. Since the proposed system operates with battery, we can evaluate its lifetime to measure current consumption. The designed system can be utilized to manage quantities of clothes and also it will be a good service to improve efficiency of laundry process.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.5
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• pp.359-368
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• 2013

Mashup is a web application that combines several different sources to create new services using Open APIs(Application Program Interfaces). Although the mashup has become very popular over the last few years, there are several challenging issues when combining a large number of APIs into the mashup, especially when composite APIs are manually integrated by mashup developers. This paper proposes a novel algorithm for automatic Open API composition. The proposed algorithm consists of constructing an operation connecting graph and searching composition candidates. We construct an operation connecting graph which is based on the semantic similarity between the inputs and the outputs of Open APIs. We generate directed acyclic graphs (DAGs) that can produce the output satisfying the desired goal. In order to produce the DAGs efficiently, we rapidly filter out APIs that are not useful for the composition. The algorithm is evaluated using a collection of REST and SOAP APIs extracted from ProgrammableWeb.com.

• The KIPS Transactions:PartB
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• v.10B no.3
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• pp.297-304
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• 2003

Nowdays, with the explosive growth of the web information, web users Increase requests of systems which collect and analyze web pages that are relevant. The systems which were develop to solve the request were used clustering methods to improve the duality of information. Clustering is defining inter relationship of unordered data and grouping data systematically. The systems using clustering provide the grouped information to the users. So, they understand the information efficiently. We proposed a hybrid clustering method to cluster a large quantity of data efficiently. By that method, We generate initial clusters using COBWEB Algorithm and refine them using Ezioni Algorithm. This paper adds two ideas in prior hybrid clustering method to increment accuracy and efficiency of clusters. Firstly, we propose the clustering method considering weight of attributes of data. Second, we redefine evaluation functions which generate initial clusters to increase efficiency in clustering. Clustering method proposed in this paper processes a large quantity of data and diminish of dependancy on sequence of input of data. So the clusters are useful to make user profiles in high quality. Ultimately, we will show that the proposed clustering method outperforms the pervious clustering method in the aspect of precision and execution speed.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.11
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• pp.2091-2096
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• 2008

Due to the improvement of mobile device capabilities, a demand for various contents service is increasing. But the differences from heterogeneous mobile devices force to develop contents which is dependent on a mobile. To solve this problem, adaptation course that reorganize contents by the device capability is hooded. In this course, device description is described using device description language but there are some problems that is absence of device description repository and the way to get device description data. In this paper, I suggest device description acquisition module and define the interfaces to access device description repository that I designed and implemented.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.12 no.1
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• pp.46-52
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• 2008

In this paper, we present the Mont-Saint-Michel virtual reality system designed to create the virtual heritage environment, which is enriched with personalized tour guide service. The tour guide system allows users to travel in the virtual heritage site and get more information about the sites or items of user's interests. It also allows users to make their own tour guidebook with the pictures they have taken during the virtual tour and more detail descriptions from the tour guide database. It then generates the web-based tour guidebook for users to utilize it for the actual site visit or share it with others over the Internet. The components of this system are designed with the consideration of reusability to be used for other interactive tour guide systems. This paper describes the motivation the development and a preliminary user study of Mont-Saint-Michel virtual reality personalized tour guide system.

• Journal of the Korea Convergence Society
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• v.9 no.12
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• pp.39-45
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• 2018

Twitter users use 'Following', 'Retweet' and so on to find tweets that they are interested in. However, it is difficult for users to find tweets that are of interest to them on Twitter, which has more than 300 million users. In this paper, we developed a customized tweet recommendation system to resolve it. First, we gather current trends to collect tweets that are worth recommending to users and popular tweets that talk about trends. Later, to analyze users and recommend customized tweets, the users' tweets and the collected tweets are categorized. Finally, using Web service, we recommend tweets that match with user categorization and users whose interests match. Consequentially, we recommended 67.2% of proper tweet.

• Journal of Cadastre & Land InformatiX
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• v.49 no.1
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• pp.113-121
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• 2019

The fourth industrial revolution technology focused on the fusion of infrastructure and various advanced technologies related city. Therefore, technical cooperation in various fields of research is essential. In order to activating the fourth industrial revolution technologies, it is necessary to research the state of technology in various fields. Consequently, this paper aims to analysis of domestic and foreign research trends on technology to the fourth industrial revolution using SNA and text mining for web site. We collected text, date data of research paper and report in web site for five years, that is, from January 1st in 2014 to December 31st in 2018. Next, we have deduced the major keywords in public data through analyzing the morphemes. Then we have analyzed the core and related keyword lists through an SNA. In Korea, the focus is on R&D and legal/institutional solution in relation to the fourth industrial revolution technology. On the other hand, in the case of foreign, there was focus on practical technologies for urban services in detail aspects.

• The Journal of the Korea Contents Association
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• v.21 no.11
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• pp.1-10
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• 2021

This study analyzes the use and meaning of consumer personality implication words in the review text of the Used Transaction Application . From of May 2021, the data were collected for the past six months by our Web crawler in Seoul and Gyeonggi Province, and a total of 1368 cases were collected first by random sampling, and finally 570 cases were preprocessed. The results are as follows. First, 48.2% of review texts were related to the personality of consumers even though it was a commercial platform of products. Second, the review text is mainly positive, which formed a text network structure based on the keyword 'gratitude'. Third, the review text, which implies consumer character, was divided into two groups: 'extrovert personality' and 'introvert personality' of consumers. And the individuality of the two groups worked together on the platform. In conclusion, we would like to suggest that consumer personality plays an important role in the platform transaction process, that consumer personality will play a role in the services of the platform in the future, and that consumer personality should be studied from various perspectives.

• 한국벤처창업학회:학술대회논문집
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• 2022.11a
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• pp.181-185
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• 2022

고객들은 조작된 온라인 리뷰가 범람하는 가운데 진정성과 가치를 지닌 리뷰를 보고자한다. 귀인 이론(Attribution theory)의 관점에서, 사람들은 리뷰어의 과거 평가 이력을 바탕으로 리뷰가 진정성 있는지를 판단하는 경향이 있다. 이러한 배경에서 본 연구의 목적은 리뷰어의 과거 평점 이력이 조작된 리뷰로 인식하는 것에 어떠한 영향을 미치며, 최종적으로 리뷰 유용성이 어떠한 영향을 미치는지 알아보는 것이다. 제안된 가설을 검증하기 위해 2차 데이터 분석(연구1)과 실험(연구2)을 수행했으며, 두 연구는 일관된 결과를 보여준다. 연구 1은 리뷰어의 과거 평가 이력이 리뷰 유용성에 미치는 영향을 분석하였다. 귀인이론에 근거하면, 사람들은 리뷰를 다른 목적을 가지고 작성되었다고 인식할 경우에 리뷰가 조작되었다고 생각하고, 그 리뷰가 물건이나 서비스의 진정한 가치를 평가하지 않았다고 간주한다. 따라서 해당 리뷰는 유용성이 낮게 평가되는 경향이 있다. 2차 데이터를 분석하기 위해 우리는 Python을 이용한 웹 스크레이퍼를 개발하여 TripAdvisor(TripAdvisor.com)에서 호텔 정보, 리뷰, 리뷰 정보 등의 연구 데이터를 수집하였다. 수집한 890명 리뷰어에 대한 100,621개의 리뷰를 분석하기 위해 음이항 회귀 분석을 수행하였다. 분석 결과, 평균 평점을 낮게 주는 리뷰어의 경우에 리뷰 유용성에 유의미한 영향을 미치지 않는 것으로 나타났다. 사람들은 극단적인 평점을 거의 주지 않는 리뷰어가 작성한 리뷰가 더 도움이 된다고 평가했다. 연구 2는 리뷰어의 과거 평점 이력을 기준으로 리뷰가 조작되었다고 평가하는 사람들의 인식 프로세스를 실험하였다. 실험 결과, 사람들은 리뷰어의 과거 평점 이력이 평균적으로 평점을 낮게 주는 경우에는 리뷰가 의심스럽다고 판단하지 않는 것으로 나타났다. 그리고 사람들은 리뷰어가 대부분 극단적인 평점을 주는 이력이 있다면 해당 리뷰어가 작성한 리뷰가 의심스럽다고 판단하는 것으로 나타났다. 연구2는 사람들이 리뷰어의 과거 평점 이력을 바탕으로 리뷰가 조작되었는지 또는 리뷰가 도움이 되는지 판단하는 경향이 있음을 보여준다. 본 연구는 귀인이론을 바탕으로 리뷰어의 과거 평점 이력이 리뷰 조작성에 대한 인식과 리뷰 유용성에 미치는 영향을 분석하여, 해당 연구분야에 새로운 관점을 추가한 기여점이 있다.