• The Journal of Information Systems
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• v.27 no.2
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• pp.157-173
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• 2018

Purpose Product characteristics and price value in website have strongly effects on customer satisfaction. Especially, in the online shopping site, the scarcity limits the customer's opportunity to purchase the product. Thus scarcity has been proposed as a important factor that makes the customer highly aware of the merchantability of the product. The scarcity in the web store is used as an important variable to make purchasing decisions of users easier by psychological pressure. In the case of scarce products with price discounts in online commerce, advertising formats that highlight scarcity value in the web commerce market are very effective in enhancing purchase intentions of consumers. Unlike offline stores, the importance of scarcity becomes more important when reflecting the characteristics of online commerce. Therefore, this study intends to confirm the influence of the degree of price discounts and scarcity information presented by Web sites on consumer purchase behavior in Web purchase behavior. Design/methodology/approach This study conducted a web-based experimental study on price sensitivity and price discount. Therefore, we created experimental web-sites that offer two stimuli according to the discount rate. The 200 respondents were randomly assigned. The stimuli were fictitious based on tourism products. The first stimulus presented the price discount(15% discount) with basic explanation about the package of the tourist package. The stimuli assigned to the second group were used for groups with high price discount intensity(65% discount). In this way, the two stimuli clearly distinguished the level of price discount intensity. This paper conducted t-test analysis and structural equation to analyze the experiemental results after confirming the reliability and validity. Findings The results of this study are as follows. The difference in price discount intensity (15% vs 65%) with scarcity showed the mean difference among all the variables. Therefore, this study concluded that there is a significant difference between the price discount of 15% and 65% for the acquisition value and transaction value of users. In particular, consumers' purchase intention is greater and product recommendation intensity is stronger when the price discount is 65%. As a result, the high degree of the price discount intensity with scarcity exerts a greater influence on consumers' purchase intentions. Product scarcity also have a significant impact on perceived value of users. Therefore, purchase intention of customers increases when perceived value increases their profit and pleasure feeling.

• KIPS Transactions on Software and Data Engineering
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• v.12 no.9
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• pp.419-430
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• 2023

Currently, NFTs have no dominant application except for the proof of ownership for digital content, and it also have small liquidity problem, which makes their price difficult to predict. Real estate usually has very high barriers to investment due to its high pricing. Real estate can be converted into NFTs and also divided into small value fungible tokens (FTs), and it can increase the the volume of the investor community due to more liquidity and better accessibility. In this document, we implement and design a system that allows ordinary users can invest on high priced real estate utilizing Black Litterman (BL) model-based Portfolio investment interface. To this end, we target a set of real estates pegged as collateral and issue NFT for the collateral using blockchain. We use oracle to get the current real estate information and to monitor varying real estate prices. After tokenizing real estate into NFTs, we divide the NFTs into easily accessible price FTs, thereby, we can lower prices and provide large liquidity with price volatility limited. In addition, we also implemented BL based asset portfolio interface for effective portfolio composition for investing in multiple of real estates with small investments. Using BL model, investors can fix the asset portfolio. We implemented the whole system using Solidity smart contracts on Flask web framework with public data portals as oracle interfaces.

• Journal of Digital Convergence
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• v.20 no.3
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• pp.407-413
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• 2022

Existing clothing recommendation systems remain at the level of showing appropriate photos when a user selects a type of clothing he or she likes after entering his or her own body size or body size. When a user purchases clothing using such recommendation systems, there are many cases in which it does not fit or does not fit the user's body size. In this study, to solve these problems of existing clothing recommendation systems, a system was implemented in which the user receives not only size but also skin tone and recommends clothing suitable for the user's body size as well as skin tone. In this system, clothing size information obtained through web crawling was periodically stored in a database for eight male tops to recommend clothing, and the entire pixel of the clothing image was analyzed to extract color text values. In order to confirm the performance of this system, a survey was conducted on 100 male college students, and the satisfaction level was 70%. Most of the reasons for not being satisfied are that the recommended clothing is limited, so it is judged that it is necessary to expand the target clothing in the future.

• Information Systems Review
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• v.6 no.2
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• pp.137-159
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• 2004

The next generation information appliances are those that can be connected with other appliances through a wired or wireless network in order to make it possible for them to transmit and receive data between them and to be remotely controlled from inside or outside of the home. Many electronic companies have aggressively invested in developing new information appliances to take the initiative in upcoming home networking era. They require systematic methods for developing new information appliances and sharing the knowledge acquired from the methods. This paper stored the knowledge acquired from developing the information appliances and developed a knowledge management system that supports the companies to use the knowledge and develop their own information appliances. In order to acquire the knowledge, this paper applied two methods for User-Centered Design in stead of using the general ones for knowledge acquisition. This paper suggested new product ideas by analyzing and observing user actions and stored the knowledge in knowledge bases, which included Knowledge from Analyzing User Actions and Knowledge from Observing User Actions. Seven new product ideas, suggested from the User-Centered Design, were made into design mockups and their videos were produced to show the real situations where they would be used in home of the future, which were stored in the knowledge base of Knowledge from Producing New Emotive Life Videos. Finally, data on present development states of future homes in Europe and Japan and newspapers articles from domestic newspapers were collected and stored in the knowledge base of Knowledge from Surveying Technology Developments. This paper developed a web-based knowledge management system that supports the companies to use the acquired knowledge. Knowledge users can get the knowledge required for developing new information appliances and suggest their own product ideas by using the knowledge management system. This will make the results from this research not confined to a case study of product development but extended to playing a role of facilitating the development of the next generation information appliances.

• Journal of Internet Computing and Services
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• v.7 no.2
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• pp.37-52
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• 2006

A mobile device like ceil phone is the necessity of modern people, of ich con be easily connected to a wireless internet through such a mobile device. The demand for a wireless data communication is growing rapidly. However, agencies have not yet completed standardization of a markup language. Due to the development of the Mobile Device, agencies in this field have provided different data formats with each Mobile Device Platform. Traditionally, contents is hand-tailored to suit the target device. A key problem is that the characteristics and capabilities of the mobile device are too diverse to service the most suitable mobile contents. Because of these problems, the need for a re-usable document description language increases. In this paper, we defined Template file that is common data to service mobile devices. We proposed a method that could be an effective wireless web service though design and the implementation of the Call manager & the XSL Generator. In the methodology, when requesting a wireless internet service, a mobile device finds out markup language and a hardware specification of the mobile device through the Call Manager component supports. The XSL Generator component creates the XSL file dynamically that is the most suitable to a device. Finally, contents is serviced to each device by XSLT. It can generate a wireless page more easily by reusing the existing web contents through such course. Therefore, it can save the time and expense for generating a wireless page.

• The KIPS Transactions:PartA
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• v.16A no.2
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• pp.113-124
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• 2009

With increasing multicore system, much effort has been put on the performance improvement of its application. Because multicore system has multiple processing devices in one system, its processing power increases compared to the single core system. However in many cases the advantages of multicore can not be exploited fully because the existing software and hardware were designed to be suitable for single core. When the existing software runs on multicore, its performance improvement is limited by the bottleneck of sharing resources and the inefficient use of cache memory on multicore. Therefore, according as the number of core increases, it doesn't show performance improvement and shows performance drop in the worst case. In this paper we propose a method of performance improvement of multicore system by applying Flow-Level Parallelism to the existing TCP/IP network application and operating system. The proposed method sets up the execution environment so that each core unit operates independently as much as possible in network application, TCP/IP stack on operating system, device driver, and network interface. Moreover it distributes network traffics to each core unit through L2 switch. The proposed method allows to minimize the sharing of application data, data structure, socket, device driver, and network interface between each core. Also it allows to minimize the competition among cores to take resources and increase the hit ratio of cache. We implemented the proposed methods with 8 core system and performed experiment. Experimental results show that network access speed and bandwidth increase linearly according to the number of core.

• Proceedings of the Korean Society for Bio-Environment Control Conference
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• 2001.04b
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• pp.75-76
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• 2001

순환식 펄라이트재배에서 배액 재사용을 위한 양분흡수 모델링을 작성하고자 EC 처리(1.5, 1.8, 2.1, 2.4, 2.7 dSㆍm-1)를 수행하였다. 생육 중기까지 EC 수준에 따른 양액흡수량은 차이가 없었지만 중기 이후 EC가 높을수록 흡수량이 감소되는 경항을 보였다(Fig. 1). NO$_3$-N, P 및 K의 흡수량은 생육기간 동안 처리간 차이를 유지하였는데 N과 K는 생육 중기 이후 일정 수준을 유지하였으나 P는 생육기간 동안 다소 증가되는 경향을 보였다. S의 흡수량은 생육 중기 이후 모든 처리에서 급격한 감소를 보였으며 생육 후기에는 처리간에 차이가 없었다(Fig. 2). 오이의 무기이온 흡수율에서와 같이 흡수량에서도 EC간 차이를 보여 EC를 무기이온 흡수량을 추정하는 요소로 이용할 수 있을 것으로 생각되었다. 무기이온 흡수량은 모든 EC 처리간에 생육 초기에는 차이를 보이지 않았으나 생육중기 이후에는 뚜렷한 차이를 보인 후 생육 후기의 높은 농도에서 그 차이가 다소 감소되는 경향을 보였다. 단위일사량에 따른 양액흡수량과 EC를 주된 변수로 한 오이의 이온 흡수량 예측 회귀식을 작성하였는데 모든 무기이온 흡수량 추정식의 상관계수는 S를 제외한 모든 이온에서 높게 나타났는데 특히 N, P, K 및 Ca에서 높았다. S이온에서의 상관계수는 0.47로 낮게 나타났으나 각 이온들의 회귀식에 대한 상관계수는 모두 1% 수준에서 유의성을 보여 위의 모델식을 순환식 양액재배에서 무기이온 추정식으로 사용이 가능할 것으로 생각되었다(Table 1). 이를 이용한 실측치와의 비교는 신뢰구간 1%내에서 높은 정의상관을 보여 실제적인 적용이 가능할 것으로 생각되었다(Fig 3)..ble 3D)를 바탕으로 MPEG-4 시스템의 특징들을 수용하여 구성되고 BIFS와 일대일로 대응된다. 반면에 XMT-0는 멀티미디어 문서를 웹문서로 표현하는 SMIL 2.0 을 그 기반으로 하였기에 MPEG-4 시스템의 특징보다는 컨텐츠를 저작하는 제작자의 초점에 맞추어 개발된 형태이다. XMT를 이용하여 컨텐츠를 저작하기 위해서는 사용자 인터페이스를 통해 입력되는 저작 정보들을 손쉽게 저장하고 조작할 수 있으며, 또한 XMT 파일 형태로 출력하기 위한 API 가 필요하다. 이에, 본 논문에서는 XMT 형태의 중간 자료형으로의 저장 및 조작을 위하여 XML 에서 표준 인터페이스로 사용하고 있는 DOM(Document Object Model)을 기반으로 하여 XMT 문법에 적합하게 API를 정의하였으며, 또한, XMT 파일을 생성하기 위한 API를 구현하였다. 본 논문에서 제공된 API는 객체기반 제작/편집 도구에 응용되어 다양한 멀티미디어 컨텐츠 제작에 사용되었다.x factorization (NMF), generative topographic mapping (GTM)의 구조와 학습 및 추론알고리즘을소개하고 이를 DNA칩 데이터 분석 평가 대회인 CAMDA-2000과 CAMDA-2001에서 사용된cancer diagnosis 문제와 gene-drug dependency analysis 문제에 적용한 결과를 살펴본다.0$\mu$M이 적당하며, 초기배발달을 유기할 때의 효과적인 cysteamine의 농도는 25~50$\mu$M인 것으로 판단된다.N)A(N)/N을 제시하였다(A(N)=N에 대한 A값). 위의 실험식을 사용하여 헝가리산 Zempleni 시료(15%

• Journal of Intelligence and Information Systems
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• v.17 no.3
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• pp.203-219
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• 2011

Previously common users just want to watch the video contents without any specific requirements or purposes. However, in today's life while watching video user attempts to know and discover more about things that appear on the video. Therefore, the requirements for finding multimedia or browsing information of objects that users want, are spreading with the increasing use of multimedia such as videos which are not only available on the internet-capable devices such as computers but also on smart TV and smart phone. In order to meet the users. requirements, labor-intensive annotation of objects in video contents is inevitable. For this reason, many researchers have actively studied about methods of annotating the object that appear on the video. In keyword-based annotation related information of the object that appeared on the video content is immediately added and annotation data including all related information about the object must be individually managed. Users will have to directly input all related information to the object. Consequently, when a user browses for information that related to the object, user can only find and get limited resources that solely exists in annotated data. Also, in order to place annotation for objects user's huge workload is required. To cope with reducing user's workload and to minimize the work involved in annotation, in existing object-based annotation automatic annotation is being attempted using computer vision techniques like object detection, recognition and tracking. By using such computer vision techniques a wide variety of objects that appears on the video content must be all detected and recognized. But until now it is still a problem facing some difficulties which have to deal with automated annotation. To overcome these difficulties, we propose a system which consists of two modules. The first module is the annotation module that enables many annotators to collaboratively annotate the objects in the video content in order to access the semantic data using Linked Data. Annotation data managed by annotation server is represented using ontology so that the information can easily be shared and extended. Since annotation data does not include all the relevant information of the object, existing objects in Linked Data and objects that appear in the video content simply connect with each other to get all the related information of the object. In other words, annotation data which contains only URI and metadata like position, time and size are stored on the annotation sever. So when user needs other related information about the object, all of that information is retrieved from Linked Data through its relevant URI. The second module enables viewers to browse interesting information about the object using annotation data which is collaboratively generated by many users while watching video. With this system, through simple user interaction the query is automatically generated and all the related information is retrieved from Linked Data and finally all the additional information of the object is offered to the user. With this study, in the future of Semantic Web environment our proposed system is expected to establish a better video content service environment by offering users relevant information about the objects that appear on the screen of any internet-capable devices such as PC, smart TV or smart phone.

• Journal of Intelligence and Information Systems
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• v.17 no.2
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• pp.39-60
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• 2011

Since the introduction of web 2.0 technology, social network service has been recognized as the foundation of an important future information technology. The advent of web 2.0 has led to the change of content creators. In the existing web, content creators are service providers, whereas they have changed into service users in the recent web. Users share experiences with other users improving contents quality, thereby it has increased the importance of social network. As a result, diverse forms of social network service have been emerged from relations and experiences of users. Social network is a network to construct and express social relations among people who share interests and activities. Today's social network service has not merely confined itself to showing user interactions, but it has also developed into a level in which content generation and evaluation are interacting with each other. As the volume of contents generated from social network service and the number of connections between users have drastically increased, the social network extraction method becomes more complicated. Consequently the following problems for the social network extraction arise. First problem lies in insufficiency of representational power of object in the social network. Second problem is incapability of expressional power in the diverse connections among users. Third problem is the difficulty of creating dynamic change in the social network due to change in user interests. And lastly, lack of method capable of integrating and processing data efficiently in the heterogeneous distributed computing environment. The first and last problems can be solved by using FOAF, a tool for describing ontology-based user profiles for construction of social network. However, solving second and third problems require a novel technology to reflect dynamic change of user interests and relations. In this paper, we propose a novel method to overcome the above problems of existing social network extraction method by applying FOAF (a tool for describing user profiles) and RSS (a literary web work publishing mechanism) to OLAP system in order to dynamically innovate and manage FOAF. We employed data interoperability which is an important characteristic of FOAF in this paper. Next we used RSS to reflect such changes as time flow and user interests. RSS, a tool for literary web work, provides standard vocabulary for distribution at web sites and contents in the form of RDF/XML. In this paper, we collect personal information and relations of users by utilizing FOAF. We also collect user contents by utilizing RSS. Finally, collected data is inserted into the database by star schema. The system we proposed in this paper generates OLAP cube using data in the database. 'Dynamic FOAF Management Algorithm' processes generated OLAP cube. Dynamic FOAF Management Algorithm consists of two functions: one is find_id_interest() and the other is find_relation (). Find_id_interest() is used to extract user interests during the input period, and find-relation() extracts users matching user interests. Finally, the proposed system reconstructs FOAF by reflecting extracted relationships and interests of users. For the justification of the suggested idea, we showed the implemented result together with its analysis. We used C# language and MS-SQL database, and input FOAF and RSS as data collected from livejournal.com. The implemented result shows that foaf : interest of users has reached an average of 19 percent increase for four weeks. In proportion to the increased foaf : interest change, the number of foaf : knows of users has grown an average of 9 percent for four weeks. As we use FOAF and RSS as basic data which have a wide support in web 2.0 and social network service, we have a definite advantage in utilizing user data distributed in the diverse web sites and services regardless of language and types of computer. By using suggested method in this paper, we can provide better services coping with the rapid change of user interests with the automatic application of FOAF.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.57-77
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• 2013

Social media has become one of the most popular media in web and mobile application. In 2011, social networks and blogs are still the top destination of online users, according to a study from Nielsen Company. In their studies, nearly 4 in 5active users visit social network and blog. Social Networks and Blogs sites rule Americans' Internet time, accounting to 23 percent of time spent online. Facebook is the main social network that the U.S internet users spend time more than the other social network services such as Yahoo, Google, AOL Media Network, Twitter, Linked In and so on. In recent trend, most of the companies promote their products in the Facebook by creating the "Facebook Page" that refers to specific product. The "Like" option allows user to subscribed and received updates their interested on from the page. The film makers which produce a lot of films around the world also take part to market and promote their films by exploiting the advantages of using the "Facebook Page". In addition, a great number of streaming service providers allows users to subscribe their service to watch and enjoy movies and TV program. They can instantly watch movies and TV program over the internet to PCs, Macs and TVs. Netflix alone as the world's leading subscription service have more than 30 million streaming members in the United States, Latin America, the United Kingdom and the Nordics. As the matter of facts, a million of movies and TV program with different of genres are offered to the subscriber. In contrast, users need spend a lot time to find the right movies which are related to their interest genre. Recent years there are many researchers who have been propose a method to improve prediction the rating or preference that would give the most related items such as books, music or movies to the garget user or the group of users that have the same interest in the particular items. One of the most popular methods to build recommendation system is traditional Collaborative Filtering (CF). The method compute the similarity of the target user and other users, which then are cluster in the same interest on items according which items that users have been rated. The method then predicts other items from the same group of users to recommend to a group of users. Moreover, There are many items that need to study for suggesting to users such as books, music, movies, news, videos and so on. However, in this paper we only focus on movie as item to recommend to users. In addition, there are many challenges for CF task. Firstly, the "sparsity problem"; it occurs when user information preference is not enough. The recommendation accuracies result is lower compared to the neighbor who composed with a large amount of ratings. The second problem is "cold-start problem"; it occurs whenever new users or items are added into the system, which each has norating or a few rating. For instance, no personalized predictions can be made for a new user without any ratings on the record. In this research we propose a clustering method according to the users' genre interest extracted from social network service (SNS) and user's movies rating information system to solve the "cold-start problem." Our proposed method will clusters the target user together with the other users by combining the user genre interest and the rating information. It is important to realize a huge amount of interesting and useful user's information from Facebook Graph, we can extract information from the "Facebook Page" which "Like" by them. Moreover, we use the Internet Movie Database(IMDb) as the main dataset. The IMDbis online databases that consist of a large amount of information related to movies, TV programs and including actors. This dataset not only used to provide movie information in our Movie Rating Systems, but also as resources to provide movie genre information which extracted from the "Facebook Page". Formerly, the user must login with their Facebook account to login to the Movie Rating System, at the same time our system will collect the genre interest from the "Facebook Page". We conduct many experiments with other methods to see how our method performs and we also compare to the other methods. First, we compared our proposed method in the case of the normal recommendation to see how our system improves the recommendation result. Then we experiment method in case of cold-start problem. Our experiment show that our method is outperform than the other methods. In these two cases of our experimentation, we see that our proposed method produces better result in case both cases.