• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.1-17
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• 2007

A virtual enterprise (VE) can be mapped into a multi-agent system (MAS) that consists of various agents with specific role(s), communicating with each other to accomplish common goal(s). However, a MAS for enacting VE requires more advanced mechanism such as context that can guarantee autonomy and dynamism of VE members considering heterogeneity and complex structure of them. This paper is to suggest a context-based MAS as a platform for constructing and managing virtual enterprises. In the Context-based MAS a VE is a collection of Actor, Interaction (among Actors), Actor Context, and Interaction Context. It can raise the speed and correctness of decision-making and operation of VE enactment using context, i.e., information about the situation (e.g., goal, role, task, time, location, media) of Actors and Interactions, as well as simple data of their properties. The Context-based MAS for VE we proposed('VECoM') may consists of Context Ontology, Context Model, Context Analyzer, and Context Reasoner. The suggested approach and system is validated through an example where a VE tries to find a partner that could join co-development of new technology.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.254-262
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• 2009

As the trend of e-business activities develop, customers come into contact with products through on-line shopping sites and lots of customers refer product reviews before the purchasing on-line. However, as the volume of product reviews grow, it takes a great deal of time and effort for customers to read and evaluate voluminous product reviews. Lately, attention is being paid to Opinion Mining(OM) as one of the effective solutions to this problem. In this paper, we propose an efficient method for opinion sentiment classification of product reviews using product specific context information of words occurred in the reviews. We define the context information of words and propose the application of context for sentiment classification and we show the performance of our method through the experiments. Additionally, in case of word corpus construction, we propose the method to construct word corpus automatically using the review texts and review scores in order to prevent traditional manual process. In consequence, we can easily get exact sentiment polarities of opinion words in product reviews.

• The Journal of Society for e-Business Studies
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• v.21 no.3
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• pp.1-13
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• 2016

The many researches on context-aware service based on the combination of semantic technology and IoT environment are being actively done. However, the previous study exploiting ontology has limitations not to accommodate the service requirement changes due to ontology prebuilt by specific service scenario. Although the concept of cross vertical ontology has emerged in order to overcome the limitation, it has other limitations that need additional components composing service environment for expressing context information and can't represent state information of environment elements. To cope with these limitations, we propose SISO (Semantic-based IoT Service Ontology) that can represent the states of environmental element without the need for additional context-information element. To verify SISO's characteristics, we select the service scenario and present applied results. The qualitative analysis comparing with the previous study is also presented by the applied results of service scenario.

• Proceedings of the Korean Information Science Society Conference
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• 2006.06b
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• pp.199-201
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• 2006

유비쿼터스 시대의 컴퓨팅은 사용자의 의향과 상황을 인지해 동적으로 목표를 설정하고 자동으로 협력해 목표를 해결하게 된다. 다양한 형태의 Context가 개체로부터 수집될 것이며 이러한 정보를 기반으로 Domain-Specific한 지식의 효율적인 처리가 가능할 것이다. 이를 위해 다른 형태의 Context를 처리하기 위해서는 기계가 인지 가능한 형태로 변형되어야 한다. 본고에서는 다중 에이전트 시스템에서 다양한 지식일과 에이전트들간의 의미적 상호작용을 증대시키기 위한 Contents Description Model을 통하여 지식원의 활용을 원활하도록 지원하는 처리를 제시한다.

• International Journal of Fuzzy Logic and Intelligent Systems
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• v.14 no.2
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• pp.122-129
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• 2014

Effective information gathering and retrieval of the most relevant web documents on the topic of interest is difficult due to the large amount of information that exists in various formats. Current information gathering and retrieval techniques are unable to exploit semantic knowledge within documents in the "big data" environment; therefore, they cannot provide precise answers to specific questions. Existing commercial big data analytic platforms are restricted to a single data type; moreover, different big data analytic platforms are effective at processing different data types. Therefore, the development of a common big data platform that is suitable for efficiently processing various data types is needed. Furthermore, users often possess more than one intelligent device. It is therefore important to find an efficient preference profile construction approach to record the user context and personalized applications. In this way, user needs can be tailored according to the user's dynamic interests by tracking all devices owned by the user.

• Journal of the Korea Society of Computer and Information
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• v.24 no.3
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• pp.65-75
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• 2019

Non-Functional Requirements (NFR) play a crucial role during the software development process. Currently, NFRs are considered more important than Functional Requirements and can determine the success of a software system. NFRs can be very complicated to understand due to their subjective manner and especially their conflicting nature. Self-adaptive systems (SAS) are operating in dynamically changing environment. Furthermore, the configuration of the SAS systems is dynamically changing according to the current systems context. This means that the configuration that manages the trade-off between NFRs in this context may not be suitable in another. This is because the NFRs satisfaction is based on a per-context basis. Therefore, one context configuration to satisfy one NFR may produce a conflict with another NFR. Furthermore, current approaches managing Non-Functional Requirements trade-off stops managing them during the system runtime which of concern. To solve this, we propose fragmentizing the NFRs and their alternative solutions in form of Multi-entity Bayesian network fragments. Consequently, when changes occur, our system creates a situation specific Bayesian network to measure the impact of the system's conditions and environmental changes on the NFRs satisfaction. Moreover, it dynamically decides which alternative solution is suitable for the current situation.

• Journal of Korean Society of Archives and Records Management
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• v.20 no.1
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• pp.115-137
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• 2020

This study aims to examine the limitations of status that describe archives based on the Archival rules, and to propose a new method using the Records in Context - Conceptual model (RiC-CM) as a solution. Given this, the study conducted literature reviews and case studies. The solutions based on RiC-CM and its effects on the limitations of the existing environment are as follows. First, RiC-CM can describe multiple provenances about archives. This can be solved by defining individual records and provenances as "entity" and expressing their associations as relationships. The interrelation of entities alone can more accurately represent the information of provenances associated with a particular archive, making it easier to identify the overall context that makes records. Second, RiC-CM can link related files. Those that belong to a specific records group (fonds) can be resolved by assigning them to individual entities and making interrelation according to the context that makes records. This method makes it possible to serve information about the context that makes records. From the user's point of view, more options are available for searching records. Third, RiC-CM can link all relevant producer-made records related to a specific production organization. If organizations are related to each other, they can be defined as "entity," and their relationship can be expressed as "associated with." It helps to comprehensively examine the context of provenances. The findings of this study are expected to be used as a basis for future research on RiC-CM, in response to the paradigm shift for electronic records management systems.

• Communications of the Korean Institute of Information Scientists and Engineers
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• v.18 no.8
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• pp.78-89
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• 2000

Today's computers are built up from a minimal set of standard pattern recognition operations. Logic gates, such as NAND, are common examples. Biomolecular materials offer an alternative approach, both in terms of variety and context sensitivity. Enzymes, the basic switching elements in biological cells, are notable for their ability to discriminate specific molecules in a complex background and to do so in a manner that is sensitive to particular milieu features and indifferent to others, The enzyme, in effect, is a powerful context sensitivity pattern processor that in a rough way can be analogized to a neuron whose input-output behavior is controlled by enzymatic dynamics.

• Journal of Korea Multimedia Society
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• v.12 no.6
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• pp.867-875
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• 2009

More and richer information sources and services are available on the web everyday. However, harmful information, such as adult content, is not appropriate for all users, notably children. Since internet is a worldwide open network, it has a limit to regulate users providing harmful contents through each countrie's national laws or systems. Additionally it is not a desirable way of developing a certain system-specific classification technology for harmful contents, because internet users can contact with them in diverse ways, for example, porn sites, harmful spams, or peer-to-peer networks, etc. Therefore, it is being emphasized to research and develop context-based core technologies for classifying harmful contents. In this paper, we propose an efficient text filter for blocking harmful texts of web documents using context-based technologies and examine which algorithms for feature selection, the process that select content terms, as features, can be useful for text categorization in all content term occurs in documents, are suitable for classifying harmful contents through implementation and experiment.

• The KIPS Transactions:PartA
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• v.12A no.6 s.96
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• pp.477-484
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• 2005

Applications in ubiquitous environments should provide the best services to users by considering the changes of users requirements and service environments, and should adapt service behaviors to the underlying platform's behaviors according to contextual changes. To reflect users requirements actively and provide more flexible services, we propose 2-level context adaptation method for supporting dynamic application adaptability in contextual changes. We offend the range of contexts to users requirements for supporting context adaptation. It can reflect users preferences in offering application services. For application adaptability, we use adaptation policies to allow applications require how they adapt to specific contexts, and to make them react actively on such situations.