• Journal of KIISE:Software and Applications
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• v.36 no.9
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• pp.732-748
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• 2009

The technology of Semantic Web realizes the base technology for context-awareness that creates new services by dynamically and flexibly combining various resources (people, concepts, etc). According to the realization of ubiquitous computing technology, many researchers are currently working for the embodiment of web service. However, most studies of them bring about the only predefined results those are limited to the initial description by service designer. In this paper, we propose a new service supporting model to provide an automatic method for plan related tasks which achieve goal state from initial state. The inputs on an planner are intial and goal descriptions which are mapped to the current situation and to the user request respectively. The idea of the method is to infer context from world model by DL-based ontology reasoning using OWL domain ontology. The context guide services to be loaded into planner. Then, the planner searches and plans at least one service to satisfy the goal state from initial state. This is STRIPS-style backward planner, and combine OWL-S services based on AI planning theory that enabling reduced search scope of huge web-service space. Also, when feasible service do not find using pattern matching, we give user alternative services through DL-based semantic searching. The experimental result demonstrates a new possibility for realizing dynamic service modeler, compared to OWLS-XPlan, which has been known as an effective application for service composition.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.4
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• pp.1923-1931
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• 2014

A value creation is understood as important business strategy these days in both academics and industry. But this phenomenon is not fully understood based on systematized framework. In this paper, we summarized value research trend based on exploratory research and inductive reasoning by exploring both international and domestic journals. And we built a research framework that can analyze value creation between supplier and customer. Value research prior to 2004 is primarily divided into values of goods or services and relationship values. After 2004, service-dominant (SD) logic has been outlined. There are other research trends to see the relationship value in terms of relationship benefits and relationship in the network or supply chain. 4 critical resource types (financial resource, knowledge resource, efficiency resource, and intellectual resource) and 5 competence types (relational capability, collaboration capability, innovation capability, managing capability) are constructed as principal factors for value creation from inductive reasoning based upon a resource-based view (RBV) and a competence-based view (CBV). The research framework was built based on 4 resources and 4 competences.

• Proceedings of the Korea Contents Association Conference
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• 2007.11a
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• pp.65-69
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• 2007

Analyzed information from research outcomes such as papers, reports and patents is important data as an indicator for setting up the direction of future research policy, as well as is essential for active sharing and dissemination of research information and cooperative work between researchers. In this paper, as a method for presenting the analyzed information easily, accurately and systematically, we describe a method that processes the information about research outcomes into ontology-based knowledge and expands the knowledge by reasoning. Especially, we focus on the definition of analyzed information from research outcomes and queries and postprocess for obtaining the analyzed information from the ontology-based knowledge.

• Journal of Korean Home Economics Education Association
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• v.6 no.2
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• pp.109-131
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• 1994

This study developed and proposed a lesson plan for the area of “Human development and family relationship”in secondary home economics curriculum. In current educational practice in secondary home economics curriculum, the employed goal and the nature of home economics are neither stated specifically nor closely interrelated. This problem has led us not being able to achieve pursuing goal of home economics education and to employ appropriate teaching methods. In view of this situation, the purpose of this study was to propose a lesson plan reflecting the contents and teaching methods to overcome difficulties and inefficiency in the current practice of secondary home economics education. The theoretical background of the lesson plan was based on the Marjorie M. Brown’s philosophy of home economics which can be summerized as follows: 1. The goal of home economics is to help individuals and families to become autonomous in their own family life and to be more capable of interacting with others in behalf of well-being of the family and of social evolution toward a free society. 2. The characteristics of home economics is conceptualized as practical science and personal service profession. 3. the nature of problems which home economics should deal with is perennial and practial. 4. Practial reasoning composed of historical understanding, critical action, and reflective thinking is appropriate for the previously mentioned goal and characteristics of home economics and for dealing with perennial practial problems. The lesson plan was proposed for one of perennial problem, “How should we understand, create, and maintain our family culture\ulcorner”by employing practial reasoning and teaching models such as “role play”and “classroom meeting.”

• The Journal of Korean Institute of Communications and Information Sciences
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• v.32 no.6A
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• pp.550-557
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• 2007

We predict a context of various structures by using Bayesian Networks Algorithms, Three-Dimensional Structures Algorithms and Genetic Algorithms. However, these algorithms have unavoidable problems when providing a context-aware service in reality due to a lack of practicality and the delay of process time in real-time environment. As far as context-aware system for specific purpose is concerned, it is very hard to be sure about the accuracy and reliability of prediction. This paper focuses on reasoning and prediction technology which provides a stochastic mechanism for context information by incorporating various context information data. The objective of this paper is to provide optimum services to users by suggesting an intellectual reasoning and prediction based on hierarchical context information. Thus, we propose a design of user location prediction algorithm using sequential matching with n-size flexible window scheme by taking user's habit or behavior into consideration. This algorithm improves average 5.10% than traditional algorithms in the accuracy and reliability of prediction using the Flexible Window Scheme.

• Journal of Convergence for Information Technology
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• v.9 no.2
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• pp.108-114
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• 2019

In this paper, we propose an intelligent vocabulary recommendation agent that automatically provides vocabulary corresponding to game-based learners' needs and requirements in the mobile education augmented reality game environment. The proposed agent reflects the characteristics of mobile technology and augmented reality technology as much as possible. In addition, this agent includes a vocabulary reasoning module, a single game vocabulary recommendation module, a battle game vocabulary recommendation module, a learning vocabulary list Module, and a thesaurus module. As a result, game-based learners' are generally satisfied. The precision of context vocabulary reasoning and thesaurus is 4.01 and 4.11, respectively, which shows that vocabulary related to situation of game-based learner is extracted. However, In the case of satisfaction, battle game vocabulary(3.86) is relatively low compared to single game vocabulary(3.94) because it recommends vocabulary that can be used jointly among recommendation vocabulary of individual learners.

• Journal of Korea Multimedia Society
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• v.9 no.7
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• pp.904-913
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• 2006

The QoS(Quality of Service) of VoD(Video on Demand) systems can be improved by reducing the faults that the stream service request from clients is rejected by the VoD server or lost during the service. This paper proposes a model of Dynamic Workload Balancer that can adjust the workload dynamically through the periodical monitoring of the VoD system, and so increase the throughput. The proposed model runs independently from the VoD system by adopting the agent concept. The model comprises the agency part interfacing the VoD system and the intelligence part reasoning or teaming the facts required for the adjustment of workload. An experiment of implementing a simulator was conducted to see whether or not application of the proposed model to VoD system is effective. As a result of the experiment, it was found that the throughput was relatively increased when the proposed model was applied compared to existing means.

• Journal of KIISE:Computing Practices and Letters
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• v.12 no.1
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• pp.56-65
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• 2006

Recently the study on service robots has been proliferated in many fields, and there are active developments for indoor services such as supporting for elderly people. It is important for robot to recognize objects and situations appropriately for effective and accurate service. Conventional object recognition methods have been based on the pre-defined geometric models, but they have limitations in indoor environments with uncertain situation such as the target objects are occluded by other ones. In this paper we propose a Bayesian network model to reason the probability of target objects for effective detection. We model the relationships between objects by activities, which are applied to non-static environments more flexibly. Overall structure is constructed by combining common-cause structures which are the units making relationship between objects, and it makes design process more efficient. We test the performance of two Bayesian networks for verifying the proposed Bayesian network model through experiments, resulting in accuracy of $86.5\%$ and $89.6\%$ respectively.

• Journal of Fashion Business
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• v.27 no.3
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• pp.50-62
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• 2023

The e-commerce fashion market has experienced a remarkable growth, leading to an overwhelming availability of shared information and numerous choices for users. In light of this, chatbots have emerged as a promising technological solution to enhance personalized services in this context. This study aimed to develop user-product attributes for a chatbot-based personalized fashion recommendation service using big data text mining techniques. To accomplish this, over one million consumer reviews from Coupang, an e-commerce platform, were collected and analyzed using frequency analyses to identify the upper-level attributes of users and products. Attribute terms were then assigned to each user-product attribute, including user body shape (body proportion, BMI), user needs (functional, expressive, aesthetic), user TPO (time, place, occasion), product design elements (fit, color, material, detail), product size (label, measurement), and product care (laundry, maintenance). The classification of user-product attributes was found to be applicable to the knowledge graph of the Conversational Path Reasoning model. A testing environment was established to evaluate the usefulness of attributes based on real e-commerce users and purchased product information. This study is significant in proposing a new research methodology in the field of Fashion Informatics for constructing the knowledge base of a chatbot based on text mining analysis. The proposed research methodology is expected to enhance fashion technology and improve personalized fashion recommendation service and user experience with a chatbot in the e-commerce market.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.205-211
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• 2012

In this paper, we proposed a context-aware augmented reality platform for mobile augmented reality to support user-oriented virtual world information for smartphone user. We designed the platform architecture and 6 subsystems which are derived from the analysis of existing augmented reality applications and platforms. The proposed architecture includes a context reasoning service subsystem for the context-aware information filtering, and separates the inner platform from the outer virtual world network containing virtual information to resolve interoperability issue of POI(Points of Interest) data.