• Journal of Korean Society of Industrial and Systems Engineering
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• v.35 no.3
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• pp.110-117
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• 2012

A product family design has received much attention over the last several decades, since a product family-based development shortens lead-times and reduces cost, as well as increases efficiency and effectiveness of the product realization process. It is challenging work, however, to define the product family design in the heterogeneous product development environments, due to myriads of products related information described in different ways across products in any companies. In this paper, we provided a way of defining product family design framework using formal concept analysis and ontology language. Based on this, the specific product family can be derived by ontological reasoning, and the new product concept can be also expanded in the framework. The proposed framework is formalized using OWL (Web Ontology Language) and implemented in $Prot{\acute{e}}g{\acute{e}}$. Actual product family design algorithm is carried out using FaCT++ engine, a plug-in to $Prot{\acute{e}}g{\acute{e}}$, and the benefits of the proposed method are also demonstrated through a case study.

• Journal of KIISE
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• v.45 no.2
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• pp.113-125
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• 2018

Recently, with the advent of the Big Data era, we have gained the capability of acquiring vast amounts of knowledge from various fields. The collected knowledge is expressed by well-formed formula and in particular, OWL, a standard language of ontology, is a typical form of well-formed formula. The symbolic reasoning is actively being studied using large amounts of ontology data for extracting intrinsic information. However, most studies of this reasoning support the restricted rule expression based on Description Logic and they have limited applicability to the real world. Moreover, knowledge management for inaccurate information is required, since knowledge inferred from the wrong information will also generate more incorrect information based on the dependencies between the inference rules. Therefore, this paper suggests that the SWAT, knowledge management system should be combined with the SWRL (Semantic Web Rule Language) reasoning based on ATMS (Assumption-based Truth Maintenance System). Moreover, this system was constructed by combining with SWRL reasoning and ATMS for managing large ontology data based on the distributed In-memory framework. Based on this, the ATMS monitoring system allows users to easily detect and correct wrong knowledge. We used the LUBM (Lehigh University Benchmark) dataset for evaluating the suggested method which is managing the knowledge through the retraction of the wrong SWRL inference data on large data.

• Journal of Korea Society of Industrial Information Systems
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• v.16 no.2
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• pp.73-83
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• 2011

In the manufacturing system, production-planning is very important in effective management for expensive production facilities and machineries. To enhance efficiency of Manufacturing Execution System(MES), a manufacturing system that reduces the difference between planning and execution, certain production-planning needs a dispatching rule that is properly designed for characteristic of work information and there should be a appropriate selection for the rule as well. Therefore, in this paper dispatching rule will be selected by several simulations based on characteristics of work information derived from process planning data. By constructing information that are from simulation into ontology, one of the knowledge-based-reasoning, production planning platform based on the selection of dispatching rule will be demonstrated. The platform has strength in its wider usage that is not limited to where it is applied. To demonstrate the platform, RacerPro and Prot$\acute{e}$g$\acute{e}$ are used in parts of ontology reasoning, and JAVA and FlexChart were applied for production-planning simulation.

• Journal of KIISE
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• v.43 no.4
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• pp.470-479
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• 2016

As the number of various types of media data such as UCC (User Created Contents) increases, research is actively being carried out in many different fields so as to provide meaningful media services. Amidst these studies, a semantic web-based media classification approach has been proposed; however, it encounters some limitations in video classification because of its underlying ontology derived from meta-information such as video tag and title. In this paper, we define recognized objects in a video and activity that is composed of video objects in a shot, and introduce a reasoning approach based on description logic. We define sequential rules for a sequence of shots in a video and describe how to classify it. For processing the large amount of increasing media data, we utilize Spark streaming, and a distributed in-memory big data processing framework, and describe how to classify media data in parallel. To evaluate the efficiency of the proposed approach, we conducted an experiment using a large amount of media ontology extracted from Youtube videos.

• Journal of KIISE:Software and Applications
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• v.35 no.6
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• pp.366-373
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• 2008

The web ontology language(OWL) has been used by ontology designers to construct ontology. In order to derive hidden information(concept subsumption, concept satisfiability and realization) of OWL ontology, a number of OWL reasoners have been introduced. But most reasoners simply report these information without process for any arbitrary entailment and unsatisfiable concept derived from a OWL ontologies. In this paper, we propose Minimum Expression Axiom Set(MEXS) detection and storing for debugging unsatisfiable concepts in ontology. In order to detect MEXS, we need to find axiom to cause inconsistency in ontology. Therefore, our work focused on two key aspects: given a inconsistency ontology, identifying the roots of axioms to occur unsatisfiable and derived axioms from among them; and extracting MEXS. Our results can be applicable to all application, which is at the basis of the description logic.

• Journal of the Korea Society of Computer and Information
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• v.24 no.10
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• pp.49-55
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• 2019

In this paper, we propose ontology-based recommendation system for supporting maintenance of Korean architectural heritage. This study includes the following: 1) design of ontology expressing repair information of architectural heritage, 2) creation of repair case DB, 3) creation of a recommendation system of repair method. For this study, we designed the ontology that expresses the information of Korean wooden building cultural heritage by referring to the existing heritage ontologies. Second, we created the repair information database based on the repair contents and the expert interview data provided by the National Institute of Cultural Heritage and the Cultural Heritage Administration. Third, we developed a system that recommends the repair method of Korean wooden architectural heritage with the most similar phenomena and causes. This study contributes to sharing repair knowledge and determining repair methods for architectural heritage repair.

• Smart Media Journal
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• v.13 no.6
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• pp.72-79
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• 2024

Vertical farming is one of the important solutions to overcome future food and population problems. However, underdeveloped countries can't afford due to high initial investment costs and technical huddles. To solve this problem, it is necessary to formalize the vertical farming area using ontology. In this paper, we present an ontology that includes various cultivation methods of vertical farming, connects sensors and actuates according to the methods, and recognizes and controls the cultivation environment context of the selected vertical fanning, we expect to be able to autonomously make control decisions about the context by analyzing the environmental context that is important for perceived vertical cultivation using the logical reasoning function of ontology.

• The KIPS Transactions:PartB
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• v.14B no.4
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• pp.295-302
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• 2007

It is very iterative and complicated work to enter the personal information every time one fills the form-based resume or one joins the new membership page on the internet. Although there are some systems that have the personal information on the computer and fill the membership page automatically, their accuracies are not often satisfactory in that the fields and their values do not match exactly. The research proposes and implements a system that has user's information on the computer and reasons and fills the information automatically that a membership web page(target page) requests using the personal information ontology. During the reasoning process, the target page is analyzed to extract the requested fields. Then the requested field names are converted to the standard field names using synonym ontology. The converted requested fields find the appropriate level in the personal information ontology using ontology match making to generate the final field value. The system not only finds the similar fields but also generates the exact field values by reasoning on the information ontology hierarchy. By experimenting with several membership pages on the web, the system showed higher accuracy over the existing systems. The system can be easily applicable to the cases where one iteratively fills the same information such as resume form.

• Journal of Digital Contents Society
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• v.13 no.1
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• pp.43-52
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• 2012

For accurate search on information resources, it is needed to manage gradual changes in ontology efficiently. Recently, because ontology is often written using OWL, techniques that can manage changes in OWL documents are required. To meet these needs, in this paper, we classify changeable elements to detect changes in OWL ontology and propose a storage schema that can manage the changes according to the characteristics of each element. And we suggest the possibility of improving performance of query processing using views that provide information about classes or properties in each ontology version. The proposed storage schema stores changes in metadata associated with each ontology version. In addition, it can manage metadata that must be added or deleted through reasoning when ontology changes. So, the proposed storage schema can support queries about history of changes in ontology and provide accurate and valid metadata that is suitable for user-selected ontology version.

• Proceedings of the IEEK Conference
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• 2008.06a
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• pp.661-662
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• 2008

Nowadays world wide web has been abundunt in quantity. However, the quality decreaed. Due to the much information, we need to select search some key words and review the search results using keywords related search methods in order to obtain information users want. In this paper, we propose the system design of treatise retrieval through metadata reasoning using ontology. In the process of this design, we express a particular treatise information as semantic-based metadata using ontology instead of using simple keywords relationship which has been used conventionally.