• International Journal of Computer Science & Network Security
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• v.21 no.9
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• pp.247-260
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• 2021

Data modeling is a process of developing a model to design and develop a data system that supports an organization's various business processes. A conceptual data model represents a technology-independent specification of structure of data to be stored within a database. The model aims to provide richer expressiveness and incorporate a set of semantics to (a) support the design, control, and integrity parts of the data stored in data management structures and (b) coordinate the viewing of connections and ideas on a database. The described structure of the data is often represented in an entity–relationship (ER) model, which was one of the first data-modeling techniques and is likely to continue to be a popular way of characterizing entity classes, attributes, and relationships. This paper attempts to examine the basic ER modeling notions in order to analyze the concepts to which they refer as well as ways to represent them. In such a mission, we apply a new modeling methodology (thinging machine; TM) to ER in terms of its fundamental building constructs, representation entities, relationships, and attributes. The goal of this venture is to further the understanding of data models and enrich their semantics. Three specific contributions to modeling in this context are incorporated: (a) using the TM model's five generic actions to inject processing in the ER structure; (b) relating the single ontological element of TM modeling (i.e., a thing/machine or thimac) to ER entities and relationships; and (c) proposing a high-level integrated, extended ER model that includes structural and time-oriented notions (e.g., events or behavior).

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.25 no.1
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• pp.69-75
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• 2007

The information in physical planning field shows the socio-economic potentials of land resources while cadastral data does the physical and legal realities of the land. The two domains commonly deal with land information but have different views. Cadastre has to evolved to the multi-purpose ones which provide value-added information and support a wide spectrum of decision makers by mixing their own information with other spatial/non-spatial databases. In this context, the demands of data exchange between the two domains is growing up but this cannot be done without resolving the heterogeneity between the two information applications. Both of either discipline sees the reality within its own scope, which means each has a unique way to abstract real world phenomena to the database. The heterogeneity problem emerges when an GIS is autonomously and independently established. It causes considerable communication difficulties since heterogeneity of representations forms unique data semantics for each database. The semantic heterogeneity obviously creates an obstacle to data exchange but, at the same time, it can be a key to solve the problems too. Therefore, the study focuses on facilitating data sharing between the fields of cadastre and physical planning by resolving the semantic heterogeneity. The core job is developing a conversion mechanism of cadastral data into the information for the physical planning by DB coupling techniques.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.181-186
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• 2005

In collaborative environment, it is necessary that the participants in collaboration should share the same understanding about the semantics of terms. For example, they should know that 'Part' and 'Item' are different word-expressions for the same meaning. In this paper, we consider sharing between CAD and PDM data. In order to handle such problems in information sharing, an information system needs to automatically recognize that the terms have the same semantics. Serving this purpose, the semantic mapping logic and the ontology based mapper system is described in this paper. In the semantic mapping logic topic, we introduce our logic that consists of four modules: Character Matching, Instance Reasoning, definition comparing and Similarity Checking. In the ontology based mapper, we introduce the system architecture and the mapping procedure.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.19 no.9
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• pp.1680-1691
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• 1994

We propose an extended hypertext data model based on object oriented paradigm that can easily the real world and semantics. We use the BNF notation to formalize the model. In our model, We introduce conceptional navigation by associating semantics on links and drive intelligent navigation using weights on links to alleviate user disorientation problem which is currently somewhat vague. We functionally classify the hypertext node into three types:Indexing node, Content node, Extract node and likewise classify the link into Alink type, Rlink type, Slink type. We believe that the typed node and typed link approach accommodate efficient query/search in hypertext.

• The Journal of Information Systems
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• v.21 no.3
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• pp.137-161
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• 2012

The increasing interest in big data analysis using various data mining techniques indicates that many commercial data mining tools now need to be equipped with fundamental text analysis modules. The most essential prerequisite for accurate analysis of text documents is an understanding of the exact semantics of each term in a document. The main difficulties in understanding the exact semantics of terms are mainly attributable to homonym and synonym problems, which is a traditional problem in the natural language processing field. Some major text mining tools provide a thesaurus to solve these problems, but a thesaurus cannot be used to resolve complex synonym problems. Furthermore, the use of a thesaurus is irrelevant to the issue of homonym problems and hence cannot solve them. In this paper, we propose a semantic text mining methodology that uses ontologies to improve the quality of text mining results by resolving the semantic ambiguity caused by homonym and synonym problems. We evaluate the practical applicability of the proposed methodology by performing a classification analysis to predict customer churn using real transactional data and Q&A articles from the "S" online shopping mall in Korea. The experiments revealed that the prediction model produced by our proposed semantic text mining method outperformed the model produced by traditional text mining in terms of prediction accuracy such as the response, captured response, and lift.

• 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.

• The Transactions of the Korea Information Processing Society
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• v.6 no.1
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• pp.11-20
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• 1999

Because conventional spatial databases process the spatial information that is valid at current time, it is difficult to manage historical information efficiently which has been changed from the past to current. Recently, there are rapid increasing of interest to solve this problem so that makes databases to support historical information as well as spatial management at the same time. It can be eventually used in a various application areas. The formal semantics in a database is used to represent database structures and operations in order to prove the correctiveness of them in terms or mathematics. It also plays an important role in database to design a database and database management system. So in this paper, we suggest spatiotemporal domain, object, data, and spatiotemporal geometric/topological operations. And we not only formalize relational algebra/calculus using formal semantics for a spatiotemporal data model, but also show the example of real orld with them.

• Journal of Korea Multimedia Society
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• v.8 no.2
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• pp.269-278
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• 2005

In order to process video data effectively, it is required that the content information of video data is loaded in database and semantics-based retrieval method can be available for various queries of users. In this paper, we propose a video retrieval system which support semantics retrieval of various users for massive video data by user's keywords and comparison area learning based on automatic agent. By user's fundamental query and selection of image for key frame that extracted from query, the agent gives the detail shape for annotation of extracted key frame. Also, key frame selected by user becomes a query image and searches the most similar key frame through color histogram comparison and comparison area learning method that proposed. From experiment, the designed and implemented system showed high precision ratio in performance assessment more than 93 percents.

• The KIPS Transactions:PartA
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• v.12A no.7 s.97
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• pp.563-570
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• 2005

Hardware and software codesign framework called PeaCE(Ptolemy extension as a Cod sign Environment) allows to express both data flow and control flow. To formally verify an fFSM specification which expresses control flow in PeaCE, the step semantics of the model was defined. In this paper, we introduce the automatic verification tool developed by formal semantics of previous work. This tool uses the SMV as inner model checker md, through our tool, users can formally verify some important bugs such as race condition, ambiguous transition, and circulartransition without directly writing logical formulae.

• Korean Journal of Cognitive Science
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• v.18 no.4
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• pp.457-483
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• 2007

Database Semantics (DBS) attempts to provide a comprehensive and integrated approach to human communication which seeks theory-implementation transparency. Two key components of DBS are Word bank as a data structure and left-Associative Grammar (LAG) as an algorithm. This study aims to provide a pilot implementation of Korean in DBS. First, it is shown how the three separate modules of grammar in DBS, namely, Hear, Think, and Speak, combine to form an integrated system that simulates a cognitive agent by making use of a simple Korean sentence as an example. Second, we provide a detailed analysis of the structure in Korean that is a characteristic of Korean involving numerals, classifiers, and nouns, thereby illustrating how DBS can be applied to Korean. We also discuss an issue raised in the literature concerning a problem that arises when we try to apply the LAG algorithm to the analysis of head-final language like Korean, and then discuss some possible solution to the problem.