• Pediatric Gastroenterology, Hepatology & Nutrition
• /
• v.8 no.1
• /
• pp.49-55
• /
• 2005

Purpose: The purpose of this study was to evaluate the quality and problems of Web sites for management of childhood and adolescent obesity. Methods: We evaluated 203 Web sites identified from the search engine, Korean Yahoo, using the word of 'childhood and adolescent obesity'. 203 Web sites were classified according to medical institutions, health information Web sites, beauty shops. etc. We surveyed whether childhood and adolescent obesity distinguished with adult obesity was considered, or not. and researched the unique managements of childhood and adolescent obesity including the cardinal treatment. Results: Of the 203 Web sites, 157(77.3%) provided detailed information about treatment of obesity, 46(22.7%) provided only simple information about one. The sites providing detailed information were composed of 52.2% of oriental medicine clinics, 35.0% of clinic & hospitals including pediatric hospitals. Distribution of the sites about management of childhood and adolescent obesity distinguished with adult's one was only 23% of oriental medicine clinics, but 93% of childrens hospitals. Conclusion: Without considering the speciality of childhood obesity, inaccurate information are distributing on internet web sites. It is necessary for concern and development of advertizing system on the internet distributing accurate information about treatment of childhood obesity.

• The Journal of Korea Institute of Information, Electronics, and Communication Technology
• /
• v.8 no.2
• /
• pp.86-100
• /
• 2015

Cloud computing is a computing term that evolved in the late 2000s, based on utility and consumption of computer resources. Google say that "Cloud computing involves deploying groups of remote servers and software networks that allow different kinds of data sources be uploaded for real time processing to generate computing results without the need to store processed data on the cloud. Cloud computing relies on sharing of resources to achieve coherence and economies of scale, similar to a utility (like the electricity grid) over a network. At the foundation of cloud computing is the broader concept of converged infrastructure and shared services. Cloud computing, or in simpler shorthand just "the cloud", also focuses on maximizing the effectiveness of the shared resources." The cloud service is a smart and/or intelligent service to save private files in any device, anytime, anywhere. Dropbox, OAuth, PAClous are required that the accumulated user's data are archives with cloud service. Currently we suggest an implementation technique to process many tasks to the cloud server with a thread pooling. Thread pooling is one of efficient implementating technique for client and service environment. In this paper, to present the implementation technique we suggest three diagrams in the consideration of software engineering.

• Journal of Intelligence and Information Systems
• /
• v.17 no.1
• /
• pp.153-169
• /
• 2011

Today using Internet environment is considered absolutely essential for establishing corporate marketing strategy. Companies have promoted their products and services through various ways of on-line marketing activities such as providing gifts and points to customers in exchange for participating in events, which is based on customers' membership data. Since companies can use these membership data to enhance their marketing efforts through various data analysis, appropriate website membership management may play an important role in increasing the effectiveness of on-line marketing campaign. Despite the growing interests in proper membership management, however, there have been difficulties in identifying inappropriate members who can weaken on-line marketing effectiveness. In on-line environment, customers tend to not reveal themselves clearly compared to off-line market. Customers who have malicious intent are able to create duplicate IDs by using others' names illegally or faking login information during joining membership. Since the duplicate members are likely to intercept gifts and points that should be sent to appropriate customers who deserve them, this can result in ineffective marketing efforts. Considering that the number of website members and its related marketing costs are significantly increasing, it is necessary for companies to find efficient ways to screen and exclude unfavorable troublemakers who are duplicate members. With this motivation, this study proposes an approach for managing duplicate membership based on the social network analysis and verifies its effectiveness using membership data gathered from real websites. A social network is a social structure made up of actors called nodes, which are tied by one or more specific types of interdependency. Social networks represent the relationship between the nodes and show the direction and strength of the relationship. Various analytical techniques have been proposed based on the social relationships, such as centrality analysis, structural holes analysis, structural equivalents analysis, and so on. Component analysis, one of the social network analysis techniques, deals with the sub-networks that form meaningful information in the group connection. We propose a method for managing duplicate memberships using component analysis. The procedure is as follows. First step is to identify membership attributes that will be used for analyzing relationship patterns among memberships. Membership attributes include ID, telephone number, address, posting time, IP address, and so on. Second step is to compose social matrices based on the identified membership attributes and aggregate the values of each social matrix into a combined social matrix. The combined social matrix represents how strong pairs of nodes are connected together. When a pair of nodes is strongly connected, we expect that those nodes are likely to be duplicate memberships. The combined social matrix is transformed into a binary matrix with '0' or '1' of cell values using a relationship criterion that determines whether the membership is duplicate or not. Third step is to conduct a component analysis for the combined social matrix in order to identify component nodes and isolated nodes. Fourth, identify the number of real memberships and calculate the reliability of website membership based on the component analysis results. The proposed procedure was applied to three real websites operated by a pharmaceutical company. The empirical results showed that the proposed method was superior to the traditional database approach using simple address comparison. In conclusion, this study is expected to shed some light on how social network analysis can enhance a reliable on-line marketing performance by efficiently and effectively identifying duplicate memberships of websites.

• The Journal of Society for e-Business Studies
• /
• v.16 no.1
• /
• pp.49-70
• /
• 2011

While new service development has become one of the most popular topics among practitioners and academics, methodologies development for new service development is only in its infancy. Especially, despite the growing interests in open innovations that effectively utilize external resources for R&D, existing research on new service development methodology designed to use external resources is scant. This article proposes a new methodology to generate new service business models that utilize massive external resources in combination with internal resources using ICT. The "Open Collaboration Innovation Methodology (OCIM)" is built based upon the theory of open innovation model and social psychology theories on behavioral motivation for cooperation. The model begins with the procedures to identify external resources that meet service objectives and requirements, and suggests motivation, control and monitoring mechanisms to implement a new service model. A business case is followed to demonstrate the use of the model. We expect that this model can be practically used by companies that are planning for developing new business models, and will provide a better understanding on open collaboration models, collective intelligence and crowd sourcing models.

• Journal of Intelligence and Information Systems
• /
• v.18 no.3
• /
• pp.137-152
• /
• 2012

In the generation of Web 2.0, as many users start to make lots of web contents called user created contents by themselves, the World Wide Web is overflowing by countless information. Therefore, it becomes the key to find out meaningful information among lots of resources. Nowadays, the information retrieval is the most important thing throughout the whole field and several types of search services are developed and widely used in various fields to retrieve information that user really wants. Especially, the legal information search is one of the indispensable services in order to provide people with their convenience through searching the law necessary to their present situation as a channel getting knowledge about it. The Office of Legislation in Korea provides the Korean Law Information portal service to search the law information such as legislation, administrative rule, and judicial precedent from 2009, so people can conveniently find information related to the law. However, this service has limitation because the recent technology for search engine basically returns documents depending on whether the query is included in it or not as a search result. Therefore, it is really difficult to retrieve information related the law for general users who are not familiar with legal terms in the search engine using simple matching of keywords in spite of those kinds of efforts of the Office of Legislation in Korea, because there is a huge divergence between everyday words and legal terms which are especially from Chinese words. Generally, people try to access the law information using everyday words, so they have a difficulty to get the result that they exactly want. In this paper, we propose a term mapping methodology between everyday words and legal terms for general users who don't have sufficient background about legal terms, and we develop a search service that can provide the search results of law information from everyday words. This will be able to search the law information accurately without the knowledge of legal terminology. In other words, our research goal is to make a law information search system that general users are able to retrieval the law information with everyday words. First, this paper takes advantage of tags of internet blogs using the concept for collective intelligence to find out the term mapping relationship between everyday words and legal terms. In order to achieve our goal, we collect tags related to an everyday word from web blog posts. Generally, people add a non-hierarchical keyword or term like a synonym, especially called tag, in order to describe, classify, and manage their posts when they make any post in the internet blog. Second, the collected tags are clustered through the cluster analysis method, K-means. Then, we find a mapping relationship between an everyday word and a legal term using our estimation measure to select the fittest one that can match with an everyday word. Selected legal terms are given the definite relationship, and the relations between everyday words and legal terms are described using SKOS that is an ontology to describe the knowledge related to thesauri, classification schemes, taxonomies, and subject-heading. Thus, based on proposed mapping and searching methodologies, our legal information search system finds out a legal term mapped with user query and retrieves law information using a matched legal term, if users try to retrieve law information using an everyday word. Therefore, from our research, users can get exact results even if they do not have the knowledge related to legal terms. As a result of our research, we expect that general users who don't have professional legal background can conveniently and efficiently retrieve the legal information using everyday words.

• Radiation Oncology Journal
• /
• v.23 no.1
• /
• pp.22-31
• /
• 2005

Purpose : To conduct a nationwide survey on the principals in radiotherapy for rectal cancer, and produce a database of Korean Patterns of Care Study. Materials and Methods : We developed web-based Patterns of Care Study system and a national survey was conducted using random sampling based on power allocation methods. Eligible patients were who had postoperative radiotherapy for rectal cancer without gross residual tumor after surgical resection and without previous history of other cancer and radiotherapy to pelvis. Data of patients were Inputted to the web based PCS system by each investigators in 19 institutions. Results : Informations on 309 patients with rectal cancer who received radiotherapy between 1998 and 1999 were collected. Male to female ratio was 59 : 41, and the most common location of tumor was lower rectum ($46\%$). Preoperative CEA was checked in $79\%$ of cases and its value was higher than 6 ng/ml in $32\%$. Pathologic stage were I in $1.5\%$, II in $32\%$, III in $53\%$, and IV in $1.6\%$. Low anterior resection was the most common type of surgery and complete resection was peformed in $95\%$ of cases. Distal resection margin was less than 2 cm in $30\%$, and number of lymph node dissected was less than 12 in $31\%$. Chemotherapy was peformed in $91\%$ and most common regimen was 5-FU and leucovorine ($59\%$). The most common type of field arrangement used for the initial pelvic field was the four field box (Posterior-Right-Left) technique ($65.0\%$), and there was no AP-PA parallel opposing field used. Patient position was prone in $81.2\%$, and the boost field was used in $61.8\%$. To displace bowel outward, pressure modulating devices or bladder filling was used in $40.1\%$. Radiation dose was prescribed to isocenter in $45.3\%$ and to isodose line in 123 cases ($39.8\%$). Percent delivered dose over $90\%$ was achieved in $92.9\%$. Conclusion : We could find the Patterns of Care for the radiotherapy in Korean rectal cancer patients was similar to that of US national survey. The type of surgery and the regimen of chemotherapy were variable according to institutions and the variations of radiation dose and field arrangement were within acceptable range.

• Journal of Intelligence and Information Systems
• /
• v.19 no.3
• /
• pp.25-44
• /
• 2013

Accessing movie contents has become easier and increased with the advent of smart TV, IPTV and web services that are able to be used to search and watch movies. In this situation, there are increasing search for preference movie contents of users. However, since the amount of provided movie contents is too large, the user needs more effort and time for searching the movie contents. Hence, there are a lot of researches for recommendations of personalized item through analysis and clustering of the user preferences and user profiles. In this study, we propose recommendation system which uses ontology based knowledge base. Our ontology can represent not only relations between metadata of movies but also relations between metadata and profile of user. The relation of each metadata can show similarity between movies. In order to build, the knowledge base our ontology model is considered two aspects which are the movie metadata model and the user model. On the part of build the movie metadata model based on ontology, we decide main metadata that are genre, actor/actress, keywords and synopsis. Those affect that users choose the interested movie. And there are demographic information of user and relation between user and movie metadata in user model. In our model, movie ontology model consists of seven concepts (Movie, Genre, Keywords, Synopsis Keywords, Character, and Person), eight attributes (title, rating, limit, description, character name, character description, person job, person name) and ten relations between concepts. For our knowledge base, we input individual data of 14,374 movies for each concept in contents ontology model. This movie metadata knowledge base is used to search the movie that is related to interesting metadata of user. And it can search the similar movie through relations between concepts. We also propose the architecture for movie recommendation. The proposed architecture consists of four components. The first component search candidate movies based the demographic information of the user. In this component, we decide the group of users according to demographic information to recommend the movie for each group and define the rule to decide the group of users. We generate the query that be used to search the candidate movie for recommendation in this component. The second component search candidate movies based user preference. When users choose the movie, users consider metadata such as genre, actor/actress, synopsis, keywords. Users input their preference and then in this component, system search the movie based on users preferences. The proposed system can search the similar movie through relation between concepts, unlike existing movie recommendation systems. Each metadata of recommended candidate movies have weight that will be used for deciding recommendation order. The third component the merges results of first component and second component. In this step, we calculate the weight of movies using the weight value of metadata for each movie. Then we sort movies order by the weight value. The fourth component analyzes result of third component, and then it decides level of the contribution of metadata. And we apply contribution weight to metadata. Finally, we use the result of this step as recommendation for users. We test the usability of the proposed scheme by using web application. We implement that web application for experimental process by using JSP, Java Script and prot$\acute{e}$g$\acute{e}$ API. In our experiment, we collect results of 20 men and woman, ranging in age from 20 to 29. And we use 7,418 movies with rating that is not fewer than 7.0. In order to experiment, we provide Top-5, Top-10 and Top-20 recommended movies to user, and then users choose interested movies. The result of experiment is that average number of to choose interested movie are 2.1 in Top-5, 3.35 in Top-10, 6.35 in Top-20. It is better than results that are yielded by for each metadata.