• Journal of Information Technology Services
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• v.8 no.1
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• pp.203-215
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• 2009

This paper illustrates the application of co-occurrence theory to generate lightweight ontologies semi-automatically. The proposed model includes three steps of a (Semi-) Automatic creation of Ontology; (they are conceptually named as) the Syntactic-based Ontology, the Semantic-based Ontology and the Ontology Refinement. Each of these three steps are designed to interactively work together, so as to generate Lightweight Ontologies. The Syntactic-based Ontology step includes generating Association words using co-occurrence in web documents. The Semantic-based Ontology step includes the Alignment large Association words with small Ontology, through the process of semantic relations by contextual terms. Finally, the Ontology Refinement step includes the domain expert to refine the lightweight Ontologies. We also conducted a case study to generate lightweight ontologies in specific domains(news domain). In this paper, we found two directions including (1) employment co-occurrence theory to generate Syntactic-based Ontology automatically and (2) Alignment large Association words with small Ontology to generate lightweight ontologies semi-automatically. So far as the design and the generation of big Ontology is concerned, the proposed research will offer useful implications to the researchers and practitioners so as to improve the research level to the commercial use.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.16 no.1
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• pp.183-190
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• 2012

This study constructs an expert search system which has a mutual cooperation function based on thesis and author profile. The proposed methodology is as follows. First, we propose weighting method which can search a keyword and the most relevant keyword. Second, we propose a method which can search the experts efficiently with this weighting method. On the preferential basis, keywords and author profiles are extracted from the papers, and experts can be searched through this method. This system will be available to many fields of social network. However, this information is distributed to many systems. We propose a method using multi-ontology to integrate distributed data. The multi-ontology is composed of meta ontology, instance ontology, location ontology and association ontology. The association ontology is constructed through analysis of keyword association dynamically. An expert network is constructed using this multi-ontology, and this expert network can search expert through association trace of keyword. The expert network can check the detail area of expertise through the research list which is provided by the system.

• Journal of Digital Convergence
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• v.12 no.2
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• pp.327-333
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• 2014

Recently, most of computing technology is based on web. Therefore, the users register web services or needed resources, and they can find and use the registered item. These services can be used alone or can be used in combination. When the item is used in combination, the ordering and association of service is important, and an ontology that defined association of services is required. In this paper, we define association of services based on ontology, and propose a method that can be used by services integration. The proposed method provides an efficient retrieval service by compositing the ontology with the service area and data association area.

• The Journal of the Korea Contents Association
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• v.6 no.10
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• pp.25-33
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• 2006

For semantic retrieval in semantic web environment, it is an important factor to manage and manipulate distributed resources. Ontology is essential for efficient search in distributed resources, but it is almost impossible to construct an unified ontology for all distributed resources in the web. In this paper, we assumed that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and the existing RDBMS tables for semantic retrieval. Most previous studies about matching between RDBMS tables and domain ontology have extracted a local ontology from RDBMS tables at first, and conducted the matching between the local ontology and domain ontology. However in the processing of extracting a local ontology, some problems such as losing domain information can be occurred since its correlation with domain ontology has not been considered at all. In this paper, we propose a methods to prevent the loss of domain information through the similarity measure between instances of RDBMS tables and instances of ontology. And using the relational information between RDBMS tables and the relational information between classes in domain ontology, more efficient instance-based matching becomes possible.

• The Journal of Korean Association of Computer Education
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• v.12 no.6
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• pp.53-67
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• 2009

In this study we surveyed the characteristics of the Semantic Web and ontology technology, analyzing the studies which applied ontology to e-Learning. In addition, we investigated the models which should be considered in the adaptive learning, analyzing the existing adaptive learning systems. On the basis of the analysis of them, we sought the ways to apply ontology for supporting the adaptive learning in the e-learning system, designing an ontology-based adaptive learning system. The system made up for the weak points of the existing ontology-based learning systems. That is, it appropriately diagnoses learners' knowledge level of learning concepts, classifying the learning styles in detail, and providing their corresponding learning methods and content. By adapting the learning content to the learners' individual learning style and knowledge level, this system would support their learning more efficiently and more effectively.

• The KIPS Transactions:PartD
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• v.13D no.3 s.106
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• pp.299-308
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• 2006

As recently XML is becoming the standard of exchanging web documents and public documentations, XML data are increasing in many areas. To retrieve the information about XML documents efficiently, the semantic web based on the ontology is appearing. The existing ontology has been constructed manually and it was time and cost consuming. Therefore in this paper, we propose the semi-automatic ontology generation technique using the data mining technique, the association rules. The proposed method solves what type and how many conceptual relationships and determines the ontology domain level for the automatic ontology generation, using the data mining algorithm. Appying the association rules to the XML documents, we intend to find out the conceptual relationships to construct the ontology, finding the frequent patterns of XML tags in the XML documents. Using the conceptual ontology domain level extracted from the data mining, we implemented the semantic web based on the ontology by XML Topic Maps (XTM) and the topic map engine, TM4J.

• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• Journal of the Korean Society for information Management
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• v.24 no.1 s.63
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• pp.273-300
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• 2007

In this study it is intended to develop the ontology which can express the relation between objects with emphasis on the structural representation of semantics. Its interoperability with other kinds of previous ontology and metadata was also considered so that the developed ontology may be applicable to the real situation. The ABC Ontology can get extended into another field where the application of the concept of event is Possible, for ABC Ontology Provides the fundamental framework on the axis of event. In this study it is Music where ABC Ontology can be applied properly, which results in creating Music Ontology. Music Ontology Provides the infrastructure of knowledge for reasoning of Potential meaning as well as the simple semantic connection of terms. The extended model of ABC Ontology has been developed by applying Music Ontology, which is the domain ontology and conveys meaning, to ABC Ontology that represents the whole framework. The representation of conceptual relation in ABC Ontology turns into the association of the framework and meaning in the extended model of ABC Ontology, with reasoning rules which are typical in ontology Also, interoperability of the extended model of ABC Ontology is examined in consideration of co-operating with metadata different from those in it.

• The Journal of the Korea Contents Association
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• v.9 no.6
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• pp.45-52
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• 2009

Recently, we started a project development of the digital expert system for the product design supporting in manufacturing industry. This digital expert system is used to the engineers in manufacturing industry for the process control, production management and system management. In this paper, we develop the ontology based inference engine shell for building of expert system. This expert system shell included a various functions which of Korean language supporting, graphical ontology map modeling interface, fuzzy rule definition function and etc. And, we introduce the knowledge representation method for the ontology map building and ontology based fuzzy inferencing method.

• Journal of the Korean Association of Geographic Information Studies
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• v.12 no.4
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• pp.146-157
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• 2009

In order to implement ontology data searching system, this paper uses some methods that effectively analyse searching options/key words with event process model and design pattern. I will propose some techniques on object-oriented process model that should improve reusability of system and reusability of ontology data which users can obtain more precise searching results. This paper shows that ontology-based data searching can assure users of the precision of searching results. Therefore, ontology-based data searching system on object-oriented design pattern is expected to show high stability and reliability, enhance reusability and scalability of modules and softwares and provide reliable data searching results to users.