• The Journal of Society for e-Business Studies
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• v.14 no.2
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• pp.95-116
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• 2009

Ontologies have provided supports in integrating heterogeneous and distributed information. More and more ontologies and tools have been developed in various domains. However, building ontologies requires much time and effort. Therefore, ontologies need to be shared and reused among users. Specifically, finding the desired ontology from an ontology repository will benefit users. In the past, most of the studies on retrieving and ranking ontologies have mainly focused on lexical level supports. In those cases, it is impossible to find an ontology that includes concepts that users want to use at the semantic level. Most ontology libraries and ontology search engines have not provided semantic matching capability. Retrieving an ontology that users want to use requires a new ontology selection and ranking mechanism based on semantic similarity matching. We propose an ontology selection and ranking model consisting of selection criteria and metrics which are enhanced in semantic matching capabilities. The model we propose presents two novel features different from the previous research models. First, it enhances the ontology selection and ranking method practically and effectively by enabling semantic matching of taxonomy or relational linkage between concepts. Second, it identifies what measures should be used to rank ontologies in the given context and what weight should be assigned to each selection measure.

• Journal of the Korean Operations Research and Management Science Society
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• v.33 no.2
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• pp.27-44
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• 2008

Owl-based ontology is useful to realize the context-aware services which are composed of the distributed and self-configuring modules. Many ontology-based inference engines are developed to infer useful information from ontology. Since these engines show the uniqueness in terms of speed and information richness, it's difficult to ensure stable operation in providing dynamic context-aware services, especially when they should deal with the complex and big-size ontology. To provide a best inference service, the purpose of this paper is to propose a novel methodology of context-aware engine selection in a contextually prompt manner Case-based reasoning is applied to identify the causality between context and inference engined to be selected. Finally, a series of experiments is performed with a novel evaluation methodology to what extent the methodology works better than competitive methods on an actual context-aware service.

• Journal of the Korea Society of Computer and Information
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• v.13 no.3
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• pp.169-177
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• 2008

Grid resources are composed of various communication networks and operation systems. When a grid system searches and selects grid resources, which meet requirements of a grid user, existing grid resource selection systems are limited due to their storage methods for resource information. In order to select grid resources suitable for requirements of a grid user and characteristics of data, this paper constructs an ontology for grid resources and proposes an ontology-based grid resource selection system. This system provides an inference engine based on rules defined by SWRL to create a resource list. Experimental results comparing the proposed system with existing grid resource selection systems, such as the Condor-G and the Nimrod-G, verify the effectiveness of the ontology-based grid resource selection system with improved job throughput and resource utilization and reduced job loss and job processing time.

• Journal of Korea Society of Digital Industry and Information Management
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• v.9 no.3
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• pp.39-48
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• 2013

Ontology has an important role in semantic web to construct and query semantic data. When system make changes to ontologies, questions arise about versioning of these changes. Applying this changes on a dynamic environment is even more important. To apply these changes, change specification method is needed. Early studies show RDF-based syntax for the operations between old and new ontologies. When several ontology versions can be used for some query, if possible, using possible newest version ontology with prospective use is best way to process the query. Prospective use of ontology means using a newer version of an ontology with a data source that conforms to a more recent ontology. In this paper, for prospective use of ontology version, structure of change specification of class and property through several ontology versions is proposed. From this, efficient adaptive ontology version selection for a query can be possible. Algorithm for structure of version transition representation is proposed and simulation results show possible newest version number for queries.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.168-171
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• 2011

One important issue in semantic web is identification and selection of domain concepts for domain ontology learning when several hundreds or even thousands of terms are extracted and available from relevant text documents shared among the members of a domain. We present a novel domain concept acquisition and selection approach for ontology learning that uses affinity propagation algorithm, which takes as input semantic and structural similarity between pairs of extracted terms called data points. Real-valued messages are passed between data points (terms) until high quality set of exemplars (concepts) and cluster iteratively emerges. All exemplars will be considered as domain concepts for learning domain ontologies. Our empirical results show that our approach achieves high precision and recall in selection of domain concepts using less number of iterations.

• Journal of Digital Convergence
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• v.11 no.9
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• pp.147-151
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• 2013

On retrieving high frequency keywords in information retrieval system, mismatchings to user's request are problems because of the various meanings of keywords in the existing ontology configuration. In this paper, it is to construct personnel selection ontology and rules in personnel management which are composed of various concepts and knowledges based on semantic web technology and suggest selection procedures to support these rules and knowledge retrieval system to verify suitability of selection results. This system utilizes a method of extraction of speech features by using non-parametric correlation coefficient. This proposed method has been validated by showing that the result average SNR of the experiment evaluation of the proposed techniques was shown to be decreased by .752dB.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.1
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• pp.80-90
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• 2010

Performance management is very popular in business area and seems to be an exciting topic. Despite significant research efforts and myriads of performance metrics, performance management today as a rigorous approach is still in an immature state and metrics are often selected based on intuitive and heuristic approach. In a R&D sector, the difficulty to select the proper performance metrics is even more increasing due to the natural characteristics of R&D such as unique or domain-specific problems. In this paper, we present a way of presenting R&D performance framework using ontology language. Based on this, the specific metrics can be derived by reusing or inheriting the context in the framework. The proposed ontological framework is formalized using OWL(Ontology Web Language) and metrics selection rules satisfying the characteristics of R&D are represented in SWRL(Semantic Web Rule Language). Actual metrics selection procedure is carried out using JESS rule engine, a plug-in to Prot$\acute{e}$g$\acute{e}$, and illustrated with an example, incorporating a prevalent R&D performance model : TVP(Technology Value Pyramid).

• Journal of Korean Society for Geospatial Information Science
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• v.19 no.1
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• pp.13-20
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• 2011

LBS services is a user-centric location based information service, where its importance has been discussed as an essential engine in an Ubiquitous Age. We aimed to develop an ontology reasoning system that enables users to derive recommended results suitable through selection standard reasoning according to various users' preferences. In order to achieve this goal, we designed the Geo-ontology system which enabled the construction of personal characteristics of users, knowledge on personal preference and knowledge on spatial and geographical preference. We also integrated a function of reasoning relevant information through the construction of Cost Value ontology using multi-criteria decision making by giving weight according to users' preference.

• Journal of Intelligence and Information Systems
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• v.17 no.1
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• pp.37-52
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• 2011

Supply chain management is a strategic thinking which enhances the value of supply chain and adapts more promptly for the changing environment. For the seamless partnership and value creation in supply chains, information and knowledge sharing and proper partner selection criteria must be applied. Thus, the partner selection criteria are critical to maintain product quality and reliability. Each part of a product is supplied by an appropriate supply partner. The criteria for selecting partners are technological capability, quality, price, consistency, etc. In reality, the criteria for partner selection may change according to the characteristics of the components. When the part is a core component, quality factor is the top priority compared to the price. For a standardized component, lower price has a higher priority. Sometimes, unexpected case occurs such as emergency order in which the preference may shift on the top. Thus, SCM partner selection criteria must be determined dynamically according to the characteristics of part and its context. The purpose of this research is to develop an OWL model for the supply chain partnership depending on its context and characteristics of the parts. The uncertainty of variable is tackled through fuzzy logic. The parts with preference of numerical value and context are represented using OWL. Part preference is converted into fuzzy membership function using fuzzy logic. For the ontology reasoning, SWRL (Semantic Web Rule Language) is applied. For the implementation of proposed model, starter motor of an automobile is adopted. After the fuzzy ontology is constructed, the process of selecting preference-based supply partner for each part is presented.

• 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.