• Journal of the Korean Institute of Intelligent Systems
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• v.21 no.2
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• pp.276-282
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• 2011

CoreNet is a valuable resource to use in the domain of natural language processing including Korean-Chinese-Japanese multilingual text analysis, and translation among natural languages. CoreNet is mapped to SUMO in order to encourage its application in broader fields and enhance its international status as a multilingual lexical semantic network. To do this, indirect and direct mapping methodologies are used. Through the indirect mapping among CoreNet-KorLex-PWN-SUMO, we alleviate the difficulty of translating CoreNet concept terms in Korean into SUMO concepts in English, and maximize recall of SUMO concepts corresponding to the concept of CoreNet.

• The Journal of the Korea Contents Association
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• v.7 no.11
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• pp.9-22
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• 2007

While standardization and its applications for registering and sharing information resources about B2B transactions such as business documents are relatively well developed, it is not easy to register and share business process resources because there are many ways to define complex business processes using different specification(definition) languages. In practice, there are several competing business process specification languages applicable under service-oriented architecture (SOA) such as ebXML BPSS, WS-BPEL, BPMN and so on. A systematic way has to be prepared to register/share diverse and heterogeneous specifications represented using those languages. This paper demonstrates the usefulness of sharing B2B business processes by prototyping a business process registry called ebRR4BP. First of all, we designed a metadata ontology to support the registration of diverse B2B business processes. To implement the proposed metadata ontology using ebXML registries, a mapping scheme to ebXML Registry Information Model is also suggested. The ontology and mapping scheme will be a foundation for supporting common interchange of business process metadata among B2B resistries.

• Journal of Digital Convergence
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• v.15 no.10
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• pp.243-251
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• 2017

As external data have become important corporate information resources, there are growing needs to combine them with internal data. This paper proposes an ontology-based scheme to combine external data with multi-dimensional databases, which shall be called multi-dimensional event ontology. In the ontology, external data are represented as events. Event characteristics such as actors, places, times, targets are linked to dimensions of a multi-dimensional database. By mapping event characteristics to database dimensions, external event data are shared via multi-dimensional hierarchies. This paper proposes rules to synchronize information sharing in multi-dimensional event ontology such as upward event information sharing, downward event information sharing and complex event information sharing. These rules are implemented using Protege. This study has a value in suggesting Big Data information sharing processes using an event database framework.

• 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.

• ETRI Journal
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• v.44 no.4
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• pp.573-587
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• 2022

The agricultural sector is completely different from other sectors since it completely relies on various natural and climatic factors. Climate changes have many effects, including lack of annual rainfall and pests, heat waves, changes in sea level, and global ozone/atmospheric CO₂ fluctuation, on land and agriculture in similar ways. Climate change also affects the environment. Based on these factors, farmers chose their crops to increase productivity in their fields. Many existing agricultural ontologies are either domain-specific or have been created with minimal vocabulary and no proper evaluation framework has been implemented. A new agricultural ontology focused on subdomains is designed to assist farmers using Jaccard relative extractor (JRE) and Naïve Bayes algorithm. The JRE is used to find the similarity between two sentences and words in the agricultural documents and the relationship between two terms is identified via the Naïve Bayes algorithm. In the proposed method, the preprocessing of data is carried out through natural language processing techniques and the tags whose dimensions are reduced are subjected to rule-based formal concept analysis and mapping. The subdomain ontologies of weather, pest, and soil are built separately, and the overall agricultural ontology are built around them. The gold standard for the lexical layer is used to evaluate the proposed technique, and its performance is analyzed by comparing it with different state-of-the-art systems. Precision, recall, F-measure, Matthews correlation coefficient, receiver operating characteristic curve area, and precision-recall curve area are the performance metrics used to analyze the performance. The proposed methodology gives a precision score of 94.40% when compared with the decision tree(83.94%) and K-nearest neighbor algorithm(86.89%) for agricultural ontology construction.

• Proceedings of the Korea Information Processing Society Conference
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• 2009.11a
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• pp.801-802
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• 2009

Currently, XML and its schema language have become the standard for data representation and information exchange format on the current web. Unfortunately, problems happen when integrating different data sources since XML mainly supports the document structure but lack consideration on sharing knowledge of data. Meanwhile, Semantic Web technologies, such as Web Ontology Language (OWL), can include the structure as well as the semantics of the data. Therefore, finding a way to integrate XML data as OWL ontology receives a high interest nowadays. In this paper we present a mapping notation to convert XML Schema to OWL domain knowledge and an effective method to transform XML instances into OWL individuals. While keeping the XML original structure, our work also adds more semantics for the XML document. Moreover, whole of the transformation processes are done automatically without any user interference. Further, our transforming approach provides the solution for duplicate element names in XML document which has not mentioned in the previous work. Our results in existing OWL syntaxes can be loaded immediately by OWL editors and Semantic Web applications.

• Journal of KIISE:Software and Applications
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• v.33 no.9
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• pp.787-801
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• 2006

Ontology merging describes the process of integrating two ontologies into a new ontology. How this is done best is a subject of ongoing research in the Semantic Web, Data Integration, Knowledge Management System, and other ontology-related application systems. Earlier research on ontology merging, however, has studied for developing effective ontology matching approaches but missed analyzing and solving methods of problems of merging two ontologies given correspondences between them. In this paper, we propose a specific ontology merging process and a generic operator, T-MERGE, for integrating two source ontologies into a new ontology. Also, we define a taxonomy of merging conflicts which is derived from differing representations between input ontologies and a method for detecting and resolving them. Our T-MERGE operator encapsulates the process of detection and resolution of conflicts and merging two entities based on given correspondences between them. We define a data structure, MergeLog, for logging the execution of T-MERGE operator. MergeLog is used to inform detailed results of execution of merging to users or recover errors. For our experiments, we used oriental philosophy ontologies, western philosophy ontologies, Yahoo western philosophy dictionary, and Naver philosophy dictionary as input ontologies. Our experiments show that the automatic merging module compared with manual merging by a expert has advantages in terms of time and effort.

• Language and Information
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• v.14 no.2
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• pp.33-46
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• 2010

This paper introduces a new linguistic-focused approach for sentiment analysis (SA) of Korean. In order to overcome shortcomings of previous works that focused mainly on statistical methods, we made effective use of various linguistic features reflecting the nature of Korean. These features include contextual shifters, modal affixes, and the morphological dependency of chunk structures. Moreover, in order to eschew possible confusion caused by ambiguous words and to improve the results of SA, we also proposed simple adjustment methods of word senses using KOLON ontology mapping information. Through experiments we contend that effective use of linguistic features and ontological information can improve the results of sentiment analysis of Korean.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.2 no.5
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• pp.239-252
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• 2008

To facilitate the processes of e-learning resource description, discovery and reuse, e-learning objects should be appropriately described and classified using standard metadata that need to be published in a registry to reduce duplication of effort and enhance semantic interoperability. This paper describes how standard ebXML registries can be used for semantic grid computing for annotating, storing, discovering and retrieving e-learning object metadata. For semantic annotation of e-learning objects, IEEE Learning Object Metadata (LOM) is adopted as the metadata ontology. In order to support the e-learning metadata ontology in interoperable ebXML registries, a mapping scheme between LOM and ebXML Registry Information Model (RIM) is proposed. The usefulness of sharing e-learning object metadata is demonstrated by prototyping a semantic registry based on the scheme.

• Journal of KIISE:Databases
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• v.34 no.6
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• pp.528-545
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• 2007

Recently ontology has been an attractive technology along with the business strategy of providing a plenty of more intelligent services. The essential problem in application domains using ontology is that all members, agents, and application programs in the domains must share the same ontology concepts. However, a variety of mobile devices, sensing devices, and network components manufactured by various companies, a variety of common carriers, and a variety of contents providers make multiple heterogeneous ontologies more likely to coexist. We can see many past researches fallen into resolving this semantic interoperability. Such methods can be broadly classified into by-mapping, by-merging, and by-translation. In this research, we focus on by-translation among them which uses a translation rule directly made between two heterogeneous ontology data like OntoMorph. However, the manual composition of the direct translation rule is not convenient by itself and if there are N ontologies, the direct method has the rule composition complexity of $O(N^2)$ in the worst case. Therefore, in this paper we introduce the cascade composition of translation rules based on web openness in order to improve the complexity. The research result made us recognize some important factors in an ontology translation system, that is speediness of translation, and conveniency of translation rule composition, and some experiments and comparing analysis with existing methods showed that our cascade method has more conveniency with insuring the speediness and the correctness.