• ETRI Journal
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• v.44 no.5
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• pp.780-793
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• 2022

Large-scale ontology management is one of the main issues when using ontology data practically. Although many approaches have been proposed in relational database management systems (RDBMSs) or object-oriented DBMSs (OODBMSs) to develop large-scale ontology management systems, they have several limitations because ontology data structures are intrinsically different from traditional data structures in RDBMSs or OODBMSs. In addition, users have difficulty using ontology data because many terminologies (ontology nodes) in large-scale ontology data match with a given string keyword. Therefore, in this study, we propose a (graph database-based ontology management system (GOMS) to efficiently manage large-scale ontology data. GOMS uses a graph DBMS and provides new query templates to help users find key concepts or instances. Furthermore, to run queries with multiple joins and path conditions efficiently, we propose GOMS encoding as a filtering tool and develop hash-based join processing algorithms in the graph DBMS. Finally, we experimentally show that GOMS can process various types of queries efficiently.

• Journal of the Korea Society of Computer and Information
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• v.20 no.3
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• pp.29-45
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• 2015

This paper proposes an implementation of SPARQL-DL, which is a query language for OWL ontologies, for query-answering over the OWL ontologies virtually generated from existing RDBs. The proposed SPARQL-DL processor internally translates input SPARQL-DL queries into SQL queries and then executes the translated queries. There are two advantages in the query processing method. First, another repository to store OWL ontologies generated from RDBs is not required. Second, a large ABox generated from an RDB instance is able to be served without using Tableau algorithm based reasoners which have a problem in large ABox reasoning. Our algorithm for query rewriting is designed to create one corresponding SQL query from one input SPARQL-DL query to minimize the overhead by establishing connections with RDBs.

• Research in Mathematical Education
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• v.13 no.2
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• pp.151-170
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• 2009

This study reports a research which was conducted on how frequently and where the students use the unit circle method while dealing with trigonometric functions in solving the trigonometry questions. Moreover, the reasons behind the choice of the methods, which could be the unit circle method, the ratio method, or the use of trigonometric identities, are also investigated to get an insight about their understanding. In this study, the relationship between the students' choices of methods in solving questions is examined in terms of instrumental or relational understanding. This is a multi-method research which involves a range of research strategies. The research techniques used in this study are test, verbal protocol (think aloud), and interview. The test has been applied to ten tenth grade students of a public school to get students' solution processes on the paper. Later on, verbal protocol has been performed with three students of these ten who were of the upper, middle and lower sets in terms of their performance in the test. The aim was to get much deeper data on the students' thinking and reasoning. Finally, interview questions have been asked both these three students and other three from the initial ten students to question the reasons behind their answers to the trigonometry questions. Findings in general suggest that students voluntarily choose to learn instrumentally whose reasons include teachers' and students' preference for the easier option and the anxiety resulting from the external exam pressure.

• The Journal of the Korea Contents Association
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• v.14 no.10
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• pp.438-453
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• 2014

This paper proposes a system to translate an RDB into an OWL ontology which enables the users to navigate the ontology in GUI. In order to accomplish the goals mentioned previously, the system overcame two difficulties. First, our system defines a new mapping algorithm to map between DB elements and ontology ones. Comparing with existing solutions, our algorithm is able to generate ontologies from more DB structures. Second, our system provides the same data generated by a reasoner to the users. Note that this operation does not load ABox ontology on a reasoner. In addition, Tableau-based reasoners have the tractability problem on a large ABox (e.g., large ABoxes translated from DBs practically cannot be served). To solve this, our system internally runs SQL queries to retrieve the same data as the one from a reasoner every time ABox elements are queried.

• 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 Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.65-70
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• 2005

This paper introduces an approach to multi-layered product knowledge model for collaborative engineering environment. The participants in collaborative engineering want to share and reason product knowledge through internet without any heterogeneity and ambiguity. However the previous knowledge models are limited in providing those aspects. In this paper, the collaborative engineering domain is analyzed and then the product knowledge is organized into four levels such as product context model, product specific model, product design model and product manufacturing model. The four levels are represented by first-order logic in layered fashion. The concepts and the instances of a formal ontology are used for recursive representation of the four levels. The instances of the concepts of an upper level like product context model are considered as the concepts of an adjacent lower level like product specific model, and this mechanism is applied to the other levels. These logic representations are integrated with the schema and the instances of a relational database. OWL representation of the four levels is defined through the integration of the logic representation and OWL primitives. The four product knowledge models have their major representation according to the characteristics of each model. This approach enables engineer to share product knowledge through internet without any ambiguity and utilize it as basis for additional reasoning.

• Journal of Intelligence and Information Systems
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• v.5 no.1
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• pp.13-34
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• 1999

Building a knowledge base effectively has been an important research area in the expert systems field. A variety of approaches have been studied including rules, semantic networks, and frames to represent the knowledge base for expert systems. As the size and complexity of the knowledge base get larger and more complicated, the integration of knowledge based with database technology cecomes more important to process the large amount of data. However, relational database management systems show many limitations in handing the complicated human knowledge due to its simple two dimensional table structure. In this paper, we propose Object-Oriented Knowledge Store (OOKS), a knowledge base model on the basis of a frame sturcture using an object-oriented database. In the proposed model, managing rules for inferencing and facts about objects in one uniform structure, knowledge and data can be tightly coupled and the performance of reasoning can be improved. For building a knowledge base, a knowledge script file representing rules and facts is used and the script file is transferred into a frame structure in database systems. Specifically, designing a frame structure in the database model as it is, it can facilitate management and utilization of knowledge in expert systems. To test the appropriateness of the proposed knowledge base model, a prototype system has been developed using a commercial ODBMS called ObjectStore and C++ programming language.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.40 no.6
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• pp.1102-1106
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• 2015

To provide social security and for cooperative smart camera context awareness processing, each camera stores and exchange context data. For a specific event, measured values with other context data is stored RDB. RDB is transformed to ontology RDF file and is used for context reasoning. Interoperability between smart cameras conforms to ONVIF and constitutes intelligent surveillance system. To guarantee the confidentiality and integrity, securiy techniques are adopted. Security overhead between agents is analyzed in the prototype system implemented.

• The Mathematical Education
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• v.42 no.3
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• pp.353-368
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• 2003

Analogy, based on a similarity, is to infer the properties of the similar object from properties of an object. It can be a very useful thinking tool for learning mathematical patterns and laws, noticing on relational properties among various situations. The purpose of this study, when manipulating hint condition, figure and table conditions and the amount of original learning by using algebra word problems, is to verify the effects of analogical transfer in solving equivalent, isomorphic and similar problems according to the similarity of source problems and target ones. Five study questions were set up for the above purpose. It was 354 first grade students of S and G middle schools in Seoul that were experimented for this study. The data was processed by MANOVA analysis of statistical program, SPSS 10.0. The results of this studies would indicate that most of the students would be poor at solving isomorphic and similar problems in the performance of analogical transfer according to the similarity of source and target problems. Hints, figure and table conditions did not facilitate the analogical transfer. Merely, on the condition that amount of teaming was increased, analogical transfer of the students was facilitated. Therefore, it is necessary to have students do much more analogical problem-solving experience to improve their analogical reasoning ability through the instruction program development in the educational fields.

• Journal of Information Processing Systems
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• v.8 no.4
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• pp.621-652
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• 2012

Software Estimations provide an inclusive set of directives for software project developers, project managers, and the management in order to produce more realistic estimates based on deficient, uncertain, and noisy data. A range of estimation models are being explored in the industry, as well as in academia, for research purposes but choosing the best model is quite intricate. Estimation by Analogy (EbA) is a form of case based reasoning, which uses fuzzy logic, grey system theory or machine-learning techniques, etc. for optimization. This research compares the estimation accuracy of some conventional data mining models with a hybrid model. Different data mining models are under consideration, including linear regression models like the ordinary least square and ridge regression, and nonlinear models like neural networks, support vector machines, and multivariate adaptive regression splines, etc. A precise and comprehensible predictive model based on the integration of GRA and regression has been introduced and compared. Empirical results have shown that regression when used with GRA gives outstanding results; indicating that the methodology has great potential and can be used as a candidate approach for software effort estimation.