• Journal of Intelligence and Information Systems
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• v.21 no.1
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• pp.15-28
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• 2015

As personal devices and pervasive technologies for interacting with networked objects continue to proliferate, there is an unprecedented world of scattered pieces of contextualized information available. However, the explosive growth and variety of information ironically lead users and service providers to make poor decision. In this situation, recommender systems may be a valuable alternative for dealing with these information overload. But they failed to utilize various types of contextual information. In this study, we suggest a methodology for context-aware recommender systems based on the concept of contextual boundary. First, as we suggest contextual boundary-based profiling which reflects contextual data with proper interpretation and structure, we attempt to solve complexity problem in context-aware recommender systems. Second, in neighbor formation with contextual information, our methodology can be expected to solve sparsity and cold-start problem in traditional recommender systems. Finally, we suggest a methodology about context support score-based recommendation generation. Consequently, our methodology can be first step for expanding application of researches on recommender systems. Moreover, as we suggest a flexible model with consideration of new technological development, it will show high performance regardless of their domains. Therefore, we expect that marketers or service providers can easily adopt according to their technical support.

• Journal of Intelligence and Information Systems
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• v.14 no.1
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• pp.117-129
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• 2008

The cost-based scheduling work has been done in both the Operations Research (OR) and Artificial Intelligence (AI) literature. To deal with more realistic problems, AI-based heuristic scheduling approach with non-regular performance measures has been studied. However, there has been little research effort to develop a full inter-job cost propagation algorithm (CPA) for different jobs having multiple downstream and upstream activities. Without such a CPA, decision-making in scheduling heuristics relies upon local, incomplete cost information, resulting in poor schedule performance from the overall cost minimizing objective. For such a purpose, we need two types of CPAs : intra-job CPA and inter-job CPA. Whenever there is a change in cost information of an activity in a job in the process of scheduling, the intra-job CPA updates cost curves of other activities connected through temporal constraints within the same job. The inter-job CPA extends cost propagation into other jobs connected through precedence relationships. By utilizing the cost information provided by CPAs, we propose cost-based scheduling heuristics that attempt to minimize the total schedule cost. This paper develops inter-job CPAs that create and update cost curves of each activity in each search state, and propagate cost information throughout a whole network of temporal constraints. Also we propose various cost-based scheduling heuristics that attempt to minimize the total schedule cost by utilizing the cost propagation algorithm.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.10 no.11
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• pp.2091-2098
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• 2006

In this paper, it proposes a protocol of resource adaptive data dissemination for sensor nodes in a wireless sensor network. In general, each sensor node used in a wireless sensor network delivers the required information to the final destination by conducting cooperative works such as sensing, processing, and communicating each other using the battery power of a independent sensor node. So, a protocol used for transferring the acquired information to users through the wireless sensor network can minimize the power consumption of energy resource given to a sensor node. Especially, it is very important to minimize the total amount of power consumption with a method for handling the problems on implosion. data delivery overlapping, and excessive message transfer caused by message broadcasting. In this paper, for the maintaining of the shortest path between sensor nodes, maximizing of the life time of a sensor node and minimizing of communication cost, it presents a method for selecting the representative transfer node for an event arising area based on the negotiation scheme and maintaining optimal transfer path using hop and energy information. Finally, for the performance evaluation, we compare the proposed protocol to existing directed diffusion and SPIN protocol. And, with the simulation results, we show that the proposed protocol enhances the performance on the power consumption rate when the number of overall sensor nodes in a sensor network or neighbor sensor nodes in an event area are increased and on the number of messages disseminated from a sensor node.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2006.05a
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• pp.437-441
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• 2006

Wireless sensor network consists of sensor nodes which are disseminated closely to each other to collect informations for the various requests of a sensor application applied for sensing phenomenons in real world. Each sensor node delivers sensing informations to an end user by conducting cooperative works such as processing and communicating between sensor nodes. In general, the power supply of a sensor node is depends on a battery so that the power consumption of a sensor node decides the entire life time of a sensor network. To resolve the problem, optimal routing algorithm can be used for prolong the entire life time of a sensor network based on the information on the energy level of each sensor node. In this paper, different from the existing Directed Diffusion and SPTN method, we presents a data dissemination protocol based on lower-power consumption that effectively maximizes the whole life time of a sensor network using the informations on the energy level of a sensor node and shortest-path hops. With the proposed method, a data transfer path is established using the informations on the energy levels and hops, and the collected sensing information from neighboring nodes in the event-occurring area is merged with others and delivered to users through the shortest path.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.14 no.8
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• pp.1809-1818
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• 2010

In order to detect the skin color area from input images, many prior researches have divided an image into the pixels having a skin color and the other pixels. In a still image or videos, it is very difficult to exactly extract the skin pixels because lighting condition and makeup generate a various variations of skin color. In this thesis, we propose a method that improves its performance using hierarchical merging of 3D skin color model and context informations for the images having various difficulties. We first make 3D color histogram distributions using skin color pixels from many YCbCr color images and then divide the color space into 3 layers including skin color region(Skin), non-skin color region(Non-skin), skin color candidate region (Skinness). When we segment the skin color region from an image, skin color pixel and non-skin color pixels are determined to skin region and non-skin region respectively. If a pixel is belong to Skinness color region, the pixels are divided into skin region or non-skin region according to the context information of its neighbors. Our proposed method can help to efficiently segment the skin color regions from images having many distorted skin colors and similar skin colors.

• KIISE Transactions on Computing Practices
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• v.21 no.11
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• pp.681-688
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• 2015

The k nearest neighbor (k-NN) graph construction is an important operation with many web-related applications, including collaborative filtering, similarity search, and many others in data mining and machine learning. Despite its many elegant properties, the brute force k-NN graph construction method has a computational complexity of $O(n^2)$, which is prohibitive for large scale data sets. Thus, (Key, Value)-based distributed framework, MapReduce, is gaining increasingly widespread use in Locality Sensitive Hashing which is efficient for high-dimension and sparse data. Based on the two-stage strategy, we engage the locality sensitive hashing technique to divide users into small subsets, and then calculate similarity between pairs in the small subsets using a brute force method on MapReduce. Specifically, generating a candidate group stage is important since brute-force calculation is performed in the following step. However, existing methods do not prevent large candidate groups. In this paper, we proposed an efficient algorithm for approximate k-NN graph construction by regrouping candidate groups. Experimental results show that our approach is more effective than existing methods in terms of graph accuracy and scan rate.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.10
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• pp.6036-6045
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• 2014

This survey research was performed to determine the social capital that public officials generate within the relationship of the community at the individual level by performing their public office work as an administrative duty. To this end, a survey was conducted on 500 civil servants in Jeju province. The survey period was May 19-23, 2014. 476 subjects were analyzed using a T-test, One way ANOVA, and multiple regression analysis to on SPSS 19.0Win software. As a result of the analysis, 1. The norms of the community cultural, male staff participation and cooperation, and social capital level of civil servants, showed a significantly higher association than female civil servants. There was a difference between the populations of registration to an association to the work location type. In addition, the social capital increases generally as the level of the officers increases. 2. The sub-category in the social capital of a personal level on civil servants family & associates trust, participation & cooperation and neighbor trust had a positive impact on the efficiency of public services. On the other hand, community cultural associations (network) did not have an influence on efficiency.

• The KIPS Transactions:PartB
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• v.9B no.5
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• pp.625-634
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• 2002

In this paper, we conducted various experiments with Bayesian networks in order to analyze clinical data of infertility patients. With these experiments, we tried to find out inter-dependencies among important factors playing the key role in clinical pregnancy, and to compare 3 different kinds of Bayesian network classifiers (including NBN, BAN, GBN) in terms of classification performance. As a result of experiments, we found the fact that the most important features playing the key role in clinical pregnancy (Clin) are indication (IND), stimulation, age of female partner (FA), number of ova (ICT), and use of Wallace (ETM), and then discovered inter-dependencies among these features. And we made sure that BAN and GBN, which are more general Bayesian network classifiers permitting inter-dependencies among features, show higher performance than NBN. By comparing Bayesian classifiers based on probabilistic representation and reasoning with other classifiers such as decision trees and k-nearest neighbor methods, we found that the former show higher performance than the latter due to inherent characteristics of clinical domain. finally, we suggested a feature reduction method in which all features except only some ones within Markov blanket of the class node are removed, and investigated by experiments whether such feature reduction can increase the performance of Bayesian classifiers.

• The Journal of the Korea Contents Association
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• v.17 no.5
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• pp.479-490
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• 2017

The objective of this study is to examine the association of social networks and medical care utilization of elderly living alone depending on self-rated health status, and also to measure the moderating effects of welfare services for elderly. To this purpose, the data which was collected from the 2014 National Survey on Elderly in Korea was analyzed by Chi-square test and Poisson regression. According to the results, social networks and elderly welfare services affected to medical care utilization of elderly living alone, only who aware of their self-rated health status as bad. With this group, the frequency of contact with family and participation in lifelong education had a significant effect on increasing medical care utilization. In contrast, the frequency of contact with neighbors and the participation in elderly employment program were significant to reduce the utilization of medical care. Furthermore, the moderating effects of elderly welfare services were also measured that formal social gathering has an effect of increasing the medical care utilization of elderly living alone by expansion of their social networks. Based on these results, this study consequently has an implication for suggesting expansion of elderly welfare services, which might be an alternative to social networks of elderly living alone, and also for seeking the direction of political intervention that helps health promotion and disease prevention through the research of medical care utilization.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.17 no.10
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• pp.412-425
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• 2016

Recently, the influence of the residential value of new town apartment houses has been increasing in the housing market; however, there has been little study on the relationship between the housing value and customer loyalty. This study analyzed the influence of the housing value on housing satisfaction and customer loyalty. To this end, this study conducted a survey targeting 519 residents in the second term new town. Accordingly, basic statistics, reliability and hypothesis test were carried out using SPSS 21.0 and ANOVA as an analysis method. The study results are as follows. First, as a result of factor analysis of the housing value, the factor was analyzed as 6 sorts, such as safety, sociality, convenience, economic feasibility, aesthetics, and comfort. Second, safety, comfort, and convenience among the factors in the housing value were found to have a significant influence on the housing satisfaction. This means that the concepts of property and assets reflect the development of new urban city apartments. Third, a new town house purchaser's positive housing value and housing satisfaction were found to increase customer loyalty. This greater satisfaction of the current residential apartment dwellers means that they are more likely to introduce their relatives and neighbors. These results suggest that a positive outlook of a new town householder on the housing value and housing satisfaction will eventually work more on revitalizing the housing market.