• Journal of the Korean Academy of Child and Adolescent Psychiatry
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• v.22 no.1
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• pp.25-37
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• 2011

Objectives：This study was conducted to develop a Korean algorithm of pharmacological and non-pharmacological treatment strategies in attention-deficit hyperactivity disorder (ADHD) and its specific comorbid disorders (e.g. tic disorder, depressive disorder, anxiety disorder, bipolar disorder, and oppositional defiant disorder/conduct disorder). Methods：Based on a literature review and expert consensus, both paper- and web-based survey tools were developed with respect to a comprehensive range of questions. Most options were scored using a 9-point scale for rating the appropriateness of medical decisions. For the other options, the surveyed experts were asked to provide answers (e.g., duration of treatment, aver-age dosage) or check boxes to indicate their preferred answers. The survey was performed on-line in a self-administered manner. Ultimately, 49 Korean child & adolescent psychiatrists, who had been considered experts in the treatment of ADHD, vol untarily completed the questionnaire. In analyzing the responses to items rated using the 9-point scale, consensus on each option was defined as a non-random distribution of scores as determined by a chi-square test. We assigned a categorical rank (first line/preferred choice, second line/alternate choice, third line/usually inappropriate) to each option based on the 95% confidence interval around the mean rating score. Results：Specific medication strategies for key clinical situations in ADHD and its comorbid disorders were indicated and described. We organized the suggested algorithms of ADHD treatment mainly on the basis of the opinions of the Korean experts. The suggested algorithm was constructed according to the templates of the Texas Child & Adolescent medication algorithm Project (CMAP). Conclusion：We have proposed a Korean treatment algorithm for ADHD, both with and without comorbid disorders through expert consensus and a broad literature review. As the tools available for ADHD treatment evolve, this algorithm could be reorganized and modified as required to suit updated scientific and clinical research findings.

• Journal of the Korean association of regional geographers
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• v.6 no.3
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• pp.117-138
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• 2000

This study is, from the view point of constructive social studies which is the foundation of the 7th curriculum, to explore whether there is any viable program and to investigate it by which students, using photo resources in social studies, can organize their knowledge in the way of self-directed thinking. The main results are as follows: If it is a principle of knowledge construction process of constructive social studies that individual construction (cognitive construction) develops into communal construction(social construction) and yet communal construction develops itself, interacting with individual construction, it will be meet the objectives of social studies. In social studies, photos are a powerful communication tool. communicating with photos enables to invoke not only the visual aspects but also invisible aspects of social phenomena from photos. It, therefore, can help develop thinking power through inquiry learning, which is one of the emphasis of the 7th curriculum. Having analyzed photo resources appeared on the regional textbooks in elementary social studies, they have been appeared that even though the importance and amount of space photo resources occupy per page is big with regard to total resources, most of the photos failed to lad to self-directed thinking but just assistant material in stead. Besides, there appeared some problems with the title, variety, size, position, tone of color, visibility of the photos, and further with the combination of the photos. Developing of photo resources for constructive social studies is to overcome some problems inherent in current text books and to reflect the theoretical background of the 7th curriculum. To develop the sort of photo that can realize the point just mentioned, it would be highly preferable to provide photo database to facilitate study with homepage through web-based interaction. To take advantage of constructive photo resources, the instruction is strategized in four stages, intuition, conflict, accommodation, and equilibration stage. With the advancement of the era of image culture, curriculum developers are required to develop dynamic, multidimensional digital photos rather than static photos when develop text books.

• Asia pacific journal of information systems
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• v.21 no.4
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• pp.45-62
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• 2011

The notion of information systems (IS) continuance has recently emerged as one of the most important research issues in the field of IS. A great deal of research has been conducted thus far on the basis of theories adapted from various disciplines including consumer behaviors and social psychology, in addition to theories regarding information technology (IT) acceptance. This previous body of knowledge provides a robust research framework that can already account for the determination of IS continuance; however, this research points to other, thus-far-unelucidated determinant factors such as habit, which were not included in traditional IT acceptance frameworks, and also re-emphasizes the importance of emotion-related constructs such as satisfaction in addition to conscious intention with rational beliefs such as usefulness. Experiences should also be considered one of the most important factors determining the characteristics of information system (IS) continuance and the features distinct from those determining IS acceptance, because more experienced users may have more opportunities for IS use, which would allow them more frequent use than would be available to less experienced or non-experienced users. Interestingly, experience has dual features that may contradictorily influence IS use. On one hand, attitudes predicated on direct experience have been shown to predict behavior better than attitudes from indirect experience or without experience; as more information is available, direct experience may render IS use a more salient behavior, and may also make IS use more accessible via memory. Therefore, experience may serve to intensify the relationship between IS use and conscious intention with evaluations, On the other hand, experience may culminate in the formation of habits: greater experience may also imply more frequent performance of the behavior, which may lead to the formation of habits, Hence, like experience, users' activation of an IS may be more dependent on habit-that is, unconscious automatic use without deliberation regarding the IS-and less dependent on conscious intentions, Furthermore, experiences can provide basic information necessary for satisfaction with the use of a specific IS, thus spurring the formation of both conscious intentions and unconscious habits, Whereas IT adoption Is a one-time decision, IS continuance may be a series of users' decisions and evaluations based on satisfaction with IS use. Moreover. habits also cannot be formed without satisfaction, even when a behavior is carried out repeatedly. Thus, experiences also play a critical role in satisfaction, as satisfaction is the consequence of direct experiences of actual behaviors. In particular, emotional experiences such as enjoyment can become as influential on IS use as are utilitarian experiences such as usefulness; this is especially true in light of the modern increase in membership-based hedonic systems - including online games, web-based social network services (SNS), blogs, and portals-all of which attempt to provide users with self-fulfilling value. Therefore, in order to understand more clearly the role of experiences in IS continuance, analysis must be conducted under a research framework that includes intentions, habits, and satisfaction, as experience may not only have duration-based moderating effects on the relationship between both intention and habit and the activation of IS use, but may also have content-based positive effects on satisfaction. This is consistent with the basic assumptions regarding the determining factors in IS continuance as suggested by Oritz de Guinea and Markus: consciousness, emotion, and habit. The principal objective of this study was to explore and assess the effects of experiences in IS continuance, with special consideration given to conscious intentions and unconscious habits, as well as satisfaction. IN service of this goal, along with a review of the relevant literature regarding the effects of experiences and habit on continuous IS use, this study suggested a research model that represents the roles of experience: its moderating role in the relationships of IS continuance with both conscious intention and unconscious habit, and its antecedent role in the development of satisfaction. For the validation of this research model. Korean university student users of 'Cyworld', one of the most influential social network services in South Korea, were surveyed, and the data were analyzed via partial least square (PLS) analysis to assess the implications of this study. In result most hypotheses in our research model were statistically supported with the exception of one. Although one hypothesis was not supported, the study's findings provide us with some important implications. First the role of experience in IS continuance differs from its role in IS acceptance. Second, the use of IS was explained by the dynamic balance between habit and intention. Third, the importance of satisfaction was confirmed from the perspective of IS continuance with experience.

• Cartoon and Animation Studies
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• s.28
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• pp.1-25
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• 2012

The rapid digitalization across all aspects of society since 1990 led to the digitalization of cartoons. As the medium of cartoons moved from paper to the web, a powerful visual culture emerged. An encounter between cartoons and multimedia technologies has helped cartoons evolve into a video culture. Today cartoons are no longer literate culture. It is critical to pay attention to cartoons as an "expanded fest" and as visual and video culture with much broader significance. In this paper, the investigator set out to diagnose the current position of cartoons changing in the rapidly changing digital age and talk about future directions that they should pursue. Thus she discussed cases of changes from 1990 when colleges began to provide specialized education for cartoons and animation to the present day when cartoon and Multimedia Comics fests exist in addition to the digitalization of cartoons. The encounter between new technologies and cartoons broke down the conventional forms of cartoons. The massive appearance of artists that made active use of new technologies in their works, in particular, has facilitated changes to the content and forms of cartoons and the expansion of character uses. The development of high technologies extends influence to the roles of appreciators beyond the artists' works. Today readers voice their opinions about works actively, build a fan base, promote the works and artists they favor, and help them rise to stardom. As artist groups of various genres were formed, the possibilities of new stories and texts and the appearance of diverse styles and world views have expanded the essence of cartoon texts and the overall cartoon system of cartoon culture, industry, education, institution, and technology. It is expected that cartoons and Multimedia Comics will continue to make a contribution as a messenger to reflect the next generation of culture, mediate it, and communicate with it. Today there is no longer a distinction between print and video cartoons. Cartoons will expand in every field through a wide range of forms and styles, given the current situations involving installation concept cartoons, blockbuster digital videos, fancy items, and characters at theme parks based on a narrative. It is therefore necessary to diversify cartoon and Multimedia Comics education in diverse ways. Today educators are faced with a task to bring up future generations of talents who are capable of leading the culture of overall senses based on literate and video culture by incorporating humanities, social studies, and new technology education into their creative artistic abilities.

• Journal of Intelligence and Information Systems
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• v.18 no.3
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• pp.35-51
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• 2012

Cloud computing is internet-based computing where computing resources are offered over the Internet as scalable and on-demand services. In particular, in case a number of various cloud services emerge in accordance with development of internet and mobile technology, to select and provide services with which service users satisfy is one of the important issues. Most of previous works show the limitation in the degree of user satisfaction because they are based on so called concept similarity in relation to user requirements or are lack of versatility of user preferences. This paper presents cloud service selection reasoning which can be applied to the general cloud service environments including a variety of computing resource services, not limited to web services. In relation to the service environments, there are two kinds of services: atomic service and composite service. An atomic service consists of service attributes which represent the characteristics of service such as functionality, performance, or specification. A composite service can be created by composition of atomic services and other composite services. Therefore, a composite service inherits attributes of component services. On the other hand, the main participants in providing with cloud services are service users, service suppliers, and service operators. Service suppliers can register services autonomously or in accordance with the strategic collaboration with service operators. Service users submit request queries including service name and requirements to the service management system. The service management system consists of a query processor for processing user queries, a registration manager for service registration, and a selection engine for service selection reasoning. In order to enhance the degree of user satisfaction, our reasoning stands on basis of the degree of conformance to user requirements of service attributes in terms of functionality, performance, and specification of service attributes, instead of concept similarity as in ontology-based reasoning. For this we introduce so called a service attribute graph (SAG) which is generated by considering the inclusion relationship among instances of a service attribute from several perspectives like functionality, performance, and specification. Hence, SAG is a directed graph which shows the inclusion relationships among attribute instances. Since the degree of conformance is very close to the inclusion relationship, we can say the acceptability of services depends on the closeness of inclusion relationship among corresponding attribute instances. That is, the high closeness implies the high acceptability because the degree of closeness reflects the degree of conformance among attributes instances. The degree of closeness is proportional to the path length between two vertex in SAG. The shorter path length means more close inclusion relationship than longer path length, which implies the higher degree of conformance. In addition to acceptability, in this paper, other user preferences such as priority for attributes and mandatary options are reflected for the variety of user requirements. Furthermore, to consider various types of attribute like character, number, and boolean also helps to support the variety of user requirements. Finally, according to service value to price cloud services are rated and recommended to users. One of the significances of this paper is the first try to present a graph-based selection reasoning unlike other works, while considering various user preferences in relation with service attributes.

• Journal of Intelligence and Information Systems
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• v.23 no.3
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• pp.119-138
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• 2017

Recently, SNS has become an important channel for marketing as well as personal communication. However, cybercrime has also evolved with the development of information and communication technology, and illegal advertising is distributed to SNS in large quantity. As a result, personal information is lost and even monetary damages occur more frequently. In this study, we propose a method to analyze which sentences and documents, which have been sent to the SNS, are related to financial fraud. First of all, as a conceptual framework, we developed a matrix of conceptual characteristics of cybercriminality on SNS and emergency management. We also suggested emergency management process which consists of Pre-Cybercriminality (e.g. risk identification) and Post-Cybercriminality steps. Among those we focused on risk identification in this paper. The main process consists of data collection, preprocessing and analysis. First, we selected two words 'daechul(loan)' and 'sachae(private loan)' as seed words and collected data with this word from SNS such as twitter. The collected data are given to the two researchers to decide whether they are related to the cybercriminality, particularly financial fraud, or not. Then we selected some of them as keywords if the vocabularies are related to the nominals and symbols. With the selected keywords, we searched and collected data from web materials such as twitter, news, blog, and more than 820,000 articles collected. The collected articles were refined through preprocessing and made into learning data. The preprocessing process is divided into performing morphological analysis step, removing stop words step, and selecting valid part-of-speech step. In the morphological analysis step, a complex sentence is transformed into some morpheme units to enable mechanical analysis. In the removing stop words step, non-lexical elements such as numbers, punctuation marks, and double spaces are removed from the text. In the step of selecting valid part-of-speech, only two kinds of nouns and symbols are considered. Since nouns could refer to things, the intent of message is expressed better than the other part-of-speech. Moreover, the more illegal the text is, the more frequently symbols are used. The selected data is given 'legal' or 'illegal'. To make the selected data as learning data through the preprocessing process, it is necessary to classify whether each data is legitimate or not. The processed data is then converted into Corpus type and Document-Term Matrix. Finally, the two types of 'legal' and 'illegal' files were mixed and randomly divided into learning data set and test data set. In this study, we set the learning data as 70% and the test data as 30%. SVM was used as the discrimination algorithm. Since SVM requires gamma and cost values as the main parameters, we set gamma as 0.5 and cost as 10, based on the optimal value function. The cost is set higher than general cases. To show the feasibility of the idea proposed in this paper, we compared the proposed method with MLE (Maximum Likelihood Estimation), Term Frequency, and Collective Intelligence method. Overall accuracy and was used as the metric. As a result, the overall accuracy of the proposed method was 92.41% of illegal loan advertisement and 77.75% of illegal visit sales, which is apparently superior to that of the Term Frequency, MLE, etc. Hence, the result suggests that the proposed method is valid and usable practically. In this paper, we propose a framework for crisis management caused by abnormalities of unstructured data sources such as SNS. We hope this study will contribute to the academia by identifying what to consider when applying the SVM-like discrimination algorithm to text analysis. Moreover, the study will also contribute to the practitioners in the field of brand management and opinion mining.

• Cartoon and Animation Studies
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• s.36
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• pp.469-491
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• 2014

Webtoon has developed the method that makes it possible to express sound visually. Also we can also hear sound in webtoon through the development of web technology. It is natural that we analyze the sound that we can hear, but we can also analyze the sound that we can not hear. This study is based on 'dual code' in cognitive psychology. Cartoonists can make visual expression on the basis of auditive impression and memory, and readers can recall the sound through the process of memory and memory-retrieval. This study analyzes both audible sound and inaudable sound. Concise analysis owes the method to film sound theory. Three main factor, Volume, pitch, and tone are recognized by frequency in acoustics. On the other hand they are expressed by the thickness and site of line and image of sound source. The visual expression of in screen sound and off screen sound is related to the frame of comics. Generally the outside of frame means off sound, but some off sound is in the frame. In addition, horror comics use much sound for the effect of genre like horror film. When analyzing comics sound using this kinds of the method film sound analysis, we can find that webtoon has developed creative expression method comparing with simple ones of early comics. Especially arranging frames and expressing sound following and vertical moving are new ones in webtoon. Also types and arrangement of frame has been varied. BGM is the first in using audible sound and recently BGM composed mixing sound effect is being used. In addition, the program which makes it possible for readers to hear sound according to scroll moving. Especially horror genre raise the genre effects using this technology. Various methods of visualizing sound are being created, and the change shows that webtoon could be the model of convergence in contents.

• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.47-63
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• 2015

As knowledge is paid attention as a new production factor that generates added value, studies continue to apply knowledge management to business environment. In addition, as ICT (Information Communication Technology) was engrafted in business environment, it leads to increasing task efficiency and productivity of individual workers. Accordingly, the way that a business achieves its goal has changed to one in which its individual members are willing to take part in the organization and share information to create new values (Han, 2003) and studies for the system and service to support such transition are carrying out. Of late, a new concept called 'Enterprise 2.0' newly appears. It is the extension of Wen 2.0 and its technology, which focus on participation, sharing and openness, to the work environment of a business (Jung, 2013). Enterprise 2.0 is being used as a collaborative tool to prop up individual creativity and group brain power by combining Web 2.0 technologies such as blog, Wiki, RSS and tag with business software (McAfee, 2006). As Tweeter gets popular, Enterprise Microblog (EMB), which is an example of Enterprise 2.0 for business, has been developed as equivalent to Tweeter in business circle and SaaS (Software as a Service) such as Yammer was introduced The studies of EMB mainly focus on demonstrating its usability in terms of intra-firm communication and knowledge management. However existing studies lean too much towards large-sized companies and certain departments, rather than a company as a whole. Therefore, few studies have been conducted on small and medium-sized companies that have difficulty preparing separate resources and supplying exclusive workforce to introduce knowledge management. In this respect, the present study placed its analytic focus on small-sized companies actually equipped with EMB to know how they use it. And, based on the findings, this study examined their knowledge management strategies for EMB from the point of codification and personalization. Hypothesis -"as a company grows, it shifts EMB strategy from codification to personalization'- was established on the basis of reviewing precedent studies and literature. To demonstrate the hypothesis, this study analyzed the usage of EMB by small companies that have used it from foundation. For case study, the duration of the use was divided into 2 spans and longitudinal analysis was employed to examine the contents of the blogs. Using the key findings of the analysis, this study is aimed to propose practical implications for the operation of knowledge management of small-sized company and the suitable application of knowledge management system for operation Knowledge Management Strategy can be classified by codification strategy and personalization strategy (Hansen et. al., 1999), and how to manage the two strategies were always studied. Also, current studies regarding the knowledge management strategy were targeted mostly for major companies, resulting in lack of studies in how it can be applied on SMEs. This research, with the knowledge management strategy suited for SMEs, sets an Enterprise Microblog (EMB), and with the EMB applied on SMEs' Knowledge Management Strategy, it is reviewed on the perspective of SMEs' Codification and Personalization Strategies. Through the advanced research regarding Knowledge Management Strategy and EMB, the hypothesis is set that "Depending on the development of the company, the main application of EMB alters from Codification Strategy to Personalization Strategy". To check the hypothesis, SME that have used the EMB called 'Yammer' was analyzed from the date of their foundation until today. The case study has implemented longitudinal analysis which divides the period when the EMBs were used into three stages and analyzes the contents. As the result of the study, this suggests a substantial implication regarding the application of Knowledge Management Strategy and its Knowledge Management System that is suitable for SME.

• Journal of Intelligence and Information Systems
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• v.21 no.3
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• pp.101-116
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• 2015

Recently, due to the development of smart devices and social media, vast amounts of information with the various forms were accumulated. Particularly, considerable research efforts are being directed towards analyzing unstructured big data to resolve various social problems. Accordingly, focus of data-driven decision-making is being moved from structured data analysis to unstructured one. Also, in the field of recommendation system, which is the typical area of data-driven decision-making, the need of using unstructured data has been steadily increased to improve system performance. Approaches to improve the performance of recommendation systems can be found in two aspects- improving algorithms and acquiring useful data with high quality. Traditionally, most efforts to improve the performance of recommendation system were made by the former approach, while the latter approach has not attracted much attention relatively. In this sense, efforts to utilize unstructured data from variable sources are very timely and necessary. Particularly, as the interests of users are directly connected with their needs, identifying the interests of the user through unstructured big data analysis can be a crew for improving performance of recommendation systems. In this sense, this study proposes the methodology of improving recommendation system by measuring interests of the user. Specially, this study proposes the method to quantify interests of the user by analyzing user's internet usage patterns, and to predict user's repurchase based upon the discovered preferences. There are two important modules in this study. The first module predicts repurchase probability of each category through analyzing users' purchase history. We include the first module to our research scope for comparing the accuracy of traditional purchase-based prediction model to our new model presented in the second module. This procedure extracts purchase history of users. The core part of our methodology is in the second module. This module extracts users' interests by analyzing news articles the users have read. The second module constructs a correspondence matrix between topics and news articles by performing topic modeling on real world news articles. And then, the module analyzes users' news access patterns and then constructs a correspondence matrix between articles and users. After that, by merging the results of the previous processes in the second module, we can obtain a correspondence matrix between users and topics. This matrix describes users' interests in a structured manner. Finally, by using the matrix, the second module builds a model for predicting repurchase probability of each category. In this paper, we also provide experimental results of our performance evaluation. The outline of data used our experiments is as follows. We acquired web transaction data of 5,000 panels from a company that is specialized to analyzing ranks of internet sites. At first we extracted 15,000 URLs of news articles published from July 2012 to June 2013 from the original data and we crawled main contents of the news articles. After that we selected 2,615 users who have read at least one of the extracted news articles. Among the 2,615 users, we discovered that the number of target users who purchase at least one items from our target shopping mall 'G' is 359. In the experiments, we analyzed purchase history and news access records of the 359 internet users. From the performance evaluation, we found that our prediction model using both users' interests and purchase history outperforms a prediction model using only users' purchase history from a view point of misclassification ratio. In detail, our model outperformed the traditional one in appliance, beauty, computer, culture, digital, fashion, and sports categories when artificial neural network based models were used. Similarly, our model outperformed the traditional one in beauty, computer, digital, fashion, food, and furniture categories when decision tree based models were used although the improvement is very small.

• Journal of Intelligence and Information Systems
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• v.16 no.3
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• pp.181-199
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• 2010

As rapid progress of population aging and strong interest in health, the demand for new healthcare service is increasing. Until now healthcare service has provided post treatment by face-to-face manner. But according to related researches, proactive treatment is resulted to be more effective for preventing diseases. Particularly, the existing healthcare services have limitations in preventing and managing metabolic syndrome such a lifestyle disease, because the cause of metabolic syndrome is related to life habit. As the advent of ubiquitous technology, patients with the metabolic syndrome can improve life habit such as poor eating habits and physical inactivity without the constraints of time and space through u-healthcare service. Therefore, lots of researches for u-healthcare service focus on providing the personalized healthcare service for preventing and managing metabolic syndrome. For example, Kim et al.(2010) have proposed a healthcare model for providing the customized calories and rates of nutrition factors by analyzing the user's preference in foods. Lee et al.(2010) have suggested the customized diet recommendation service considering the basic information, vital signs, family history of diseases and food preferences to prevent and manage coronary heart disease. And, Kim and Han(2004) have demonstrated that the web-based nutrition counseling has effects on food intake and lipids of patients with hyperlipidemia. However, the existing researches for u-healthcare service focus on providing the predefined one-way u-healthcare service. Thus, users have a tendency to easily lose interest in improving life habit. To solve such a problem of u-healthcare service, this research suggests a u-healthcare recommender system which is based on collaborative filtering principle and social network. This research follows the principle of collaborative filtering, but preserves local networks (consisting of small group of similar neighbors) for target users to recommend context aware healthcare services. Our research is consisted of the following five steps. In the first step, user profile is created using the usage history data for improvement in life habit. And then, a set of users known as neighbors is formed by the degree of similarity between the users, which is calculated by Pearson correlation coefficient. In the second step, the target user obtains service information from his/her neighbors. In the third step, recommendation list of top-N service is generated for the target user. Making the list, we use the multi-filtering based on user's psychological context information and body mass index (BMI) information for the detailed recommendation. In the fourth step, the personal information, which is the history of the usage service, is updated when the target user uses the recommended service. In the final step, a social network is reformed to continually provide qualified recommendation. For example, the neighbors may be excluded from the social network if the target user doesn't like the recommendation list received from them. That is, this step updates each user's neighbors locally, so maintains the updated local neighbors always to give context aware recommendation in real time. The characteristics of our research as follows. First, we develop the u-healthcare recommender system for improving life habit such as poor eating habits and physical inactivity. Second, the proposed recommender system uses autonomous collaboration, which enables users to prevent dropping and not to lose user's interest in improving life habit. Third, the reformation of the social network is automated to maintain the quality of recommendation. Finally, this research has implemented a mobile prototype system using JAVA and Microsoft Access2007 to recommend the prescribed foods and exercises for chronic disease prevention, which are provided by A university medical center. This research intends to prevent diseases such as chronic illnesses and to improve user's lifestyle through providing context aware and personalized food and exercise services with the help of similar users'experience and knowledge. We expect that the user of this system can improve their life habit with the help of handheld mobile smart phone, because it uses autonomous collaboration to arouse interest in healthcare.