• Korean Journal of English Language and Linguistics
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• v.4 no.2
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• pp.151-174
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• 2004

A historical investigation reveals that English preposition with underwent a change from OPPOSITION to ASSOCIATION and further to ACCOMPANIMENT, where the first stage shows peculiarity in that the two concepts involved comprise an unusual set to form an extensional chain. Intrigued by this oddity, this paper aims to investigate the semantic structure of English preposition with from a grammaticalization perspective. We review mechanisms and models of semantic change and evaluate their adequacy with the semantic structure and change shown by with. Drawing upon the observed fact that with underwent the apparent antonymic semantic change, it is argued that such semantic change mechanisms as metaphor, metonymy, subjectification, and generalization have difficulties explaining the change, and that only the Frame-of-Focus Variation can effectively account for this peculiar change type. In terms of semantic change models, we argue that the Bleaching Model cannot effectively provide an explanation; that the Loss and Gain Model has problems in explaining the motivation of change directions; that the Metonymic-Metaphoric Model cannot be assessed at the current level of investigation; and that the Overlap Model and the Prototype Extension Model excellently account for the macro-level changes.

• Journal of Intelligence and Information Systems
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• v.19 no.1
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• pp.111-123
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• 2013

Semantic similarity/relatedness measure between two concepts plays an important role in research on system integration and database integration. Moreover, current research on keyword recommendation or tag clustering strongly depends on this kind of semantic measure. For this reason, many researchers in various fields including computer science and computational linguistics have tried to improve methods to calculating semantic similarity/relatedness measure. This study of similarity between concepts is meant to discover how a computational process can model the action of a human to determine the relationship between two concepts. Most research on calculating semantic similarity usually uses ready-made reference knowledge such as semantic network and dictionary to measure concept similarity. The topological method is used to calculated relatedness or similarity between concepts based on various forms of a semantic network including a hierarchical taxonomy. This approach assumes that the semantic network reflects the human knowledge well. The nodes in a network represent concepts, and way to measure the conceptual similarity between two nodes are also regarded as ways to determine the conceptual similarity of two words(i.e,. two nodes in a network). Topological method can be categorized as node-based or edge-based, which are also called the information content approach and the conceptual distance approach, respectively. The node-based approach is used to calculate similarity between concepts based on how much information the two concepts share in terms of a semantic network or taxonomy while edge-based approach estimates the distance between the nodes that correspond to the concepts being compared. Both of two approaches have assumed that the semantic network is static. That means topological approach has not considered the change of semantic relation between concepts in semantic network. However, as information communication technologies make advantage in sharing knowledge among people, semantic relation between concepts in semantic network may change. To explain the change in semantic relation, we adopt the cognitive semantics. The basic assumption of cognitive semantics is that humans judge the semantic relation based on their cognition and understanding of concepts. This cognition and understanding is called 'World Knowledge.' World knowledge can be categorized as personal knowledge and cultural knowledge. Personal knowledge means the knowledge from personal experience. Everyone can have different Personal Knowledge of same concept. Cultural Knowledge is the knowledge shared by people who are living in the same culture or using the same language. People in the same culture have common understanding of specific concepts. Cultural knowledge can be the starting point of discussion about the change of semantic relation. If the culture shared by people changes for some reasons, the human's cultural knowledge may also change. Today's society and culture are changing at a past face, and the change of cultural knowledge is not negligible issues in the research on semantic relationship between concepts. In this paper, we propose the future directions of research on semantic similarity. In other words, we discuss that how the research on semantic similarity can reflect the change of semantic relation caused by the change of cultural knowledge. We suggest three direction of future research on semantic similarity. First, the research should include the versioning and update methodology for semantic network. Second, semantic network which is dynamically generated can be used for the calculation of semantic similarity between concepts. If the researcher can develop the methodology to extract the semantic network from given knowledge base in real time, this approach can solve many problems related to the change of semantic relation. Third, the statistical approach based on corpus analysis can be an alternative for the method using semantic network. We believe that these proposed research direction can be the milestone of the research on semantic relation.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.21-26
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• 2006

The semantic web is an emerging paradigm in the information retrieval and Web-based system. This paper deals with a Web change detection system which employs the semantic web and ontology. While existing Web change detection systems detect the syntactic change, the proposed system focuses on the detection of the semantic change. The system detects the change only when the web has semantic change. To achieve this, the system employs the domain-specific ontology (e.g., computer science professional person information in the paper). The Web pages regarding before and after change are converted according to the ontology. Then the comparison is performed. The experimental result shows the semantic-based change detection is more useful than the syntax-based change detection.

• Journal of information and communication convergence engineering
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• v.2 no.1
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• pp.26-31
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• 2004

In the last few years, The Semantic Web has increased the interest in ontologies. Ontology is an essential component of the semantic web. Ontologies continue to change and evolve. We consider the management of versions in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. In many cases, we want to be able to search in historical versions, query changes in versions, retrieve versions on the temporal dimension. In order to support an ontology query language that supports temporal operations, we consider temporal dimension includes transaction time and valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the storage policies that are storing all the versions, all the sequence of changed element, all the change sets, the aggregation of change sets periodically, and the aggregation of change sets using a criterion. We conduct a set of experiments to compare the performance of each storage policies. We present the experimental results for evaluating the performance of different storage policies from scheme 1 to scheme 5.

• Journal of Intelligence and Information Systems
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• v.10 no.2
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• pp.111-131
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• 2004

Software change is an essential operation for software evolution. To maintain the system competently, managers as well as developers must be able to understand the structure of the system but the structure of software is hidden to the developers and managers who need to change it. In this paper, we present a system (OntCIA) for supporting change impact analysis for rating and billing domain based on the semantic web technology. The basic idea of OntCIA is to build a domain knowledge base using an OWL ontology and RDF to implement change impact analysis system that would support the managers and software developers in finding out information about structure of large software system. OntCIA allows users to incrementally build an ontology in rating and billing domain and provides useful information in response to user queries concerning the code, such as, for example 'Find the modules which have a role for confirming new subscription'. The strengths of OntCIA are its architecture for easy maintenance as well as semantic indexing by automatic reasoning.

• Journal of Information Technology Applications and Management
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• v.12 no.3
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• pp.27-39
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• 2005

The Semantic Web has increased the interest in ontologies recently Ontology is an essential component of the semantic web and continues to change and evolve. We consider versions management schemes in ontology. We study a set of changes based on domain changes, changes in conceptualization, metadata changes, and temporal dimension. Our change specification is represented by a set of changes. A set of changes consists of instance data change, structural change, and identifier change. In order to support a query in ontology versions, we consider temporal dimension includes valid time. Ontology versioning brings about massive amount of versions to be stored and maintained. We present the ontology versions management schemes that are 1) storing all the change sets, 2) storing the aggregation of change sets periodically, and 3) storing the aggregation of change sets using an adaptive criterion. We conduct a set of experiments to compare the performance of each versions management schemes. We present the experimental results for evaluating the performance of the three version management schemes from scheme 1 to scheme 3. Scheme 1 has the least storage usage. The average response time in Scheme 1 is extremely large, those of Scheme 3 is smaller than Scheme 2. Scheme 3 shows a good performance relatively.

• Cross-Cultural Studies
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• v.31
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• pp.287-308
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• 2013

Russian language tends to be quite open to borrowing. In Russian it has been for a long time the conventional way of expanding the lexicon, accepting many words from adjacent languages, including Church Slavic. In the contemporary Russian English has been the main source for loanwords. There are several linguistic factors for lexical borrowing: 1. the necessity of denominating new facts, phenomena or concepts, 2. the necessity of differentiating concepts, 3. the necessity of specializing new concepts, 4. the introduction of new international terms, 5. the increase of periphrastic expressions, 6. the needs for the more elegant and modern words. These factors have caused borrowing to enlarge the component of the lexicon and phrasal expressions, but excessive use of foreign words has brought about negative effects such as linguistic pollution. Some borrowed words are assimilated without serious conflicts, but other words undergo semantic changes in confrontation to existing words of similar meanings. These types of semantic changes comprise total change of meaning, reduction of semantic scale and extension of meaning. Semantic changes are caused by linguistic factors such as lexical conflict with existing words or by socio-culural factors such as misunderstanding of foreign words. And extension of meaning shows two types: qualitative extension and quantitative extension. The first means extending the semantic scope of a borrowed word and the latter - increasing the number of its sememe. In contemporary Russian language we can witness two productive phenomena: qualitative extension by socio-cultural factors, in which words with negative nuances are changed into those with positive ones and professional terms become common words, losing their professional meanings. On the other hand, by quantative extension some loanwords change their concrete meanings into abstract ones. In such cases loanwords acquire the additional meanings of abstractness, putting aside their original concrete meanings as the basic. On the contrary, the qualitative extension of adding the special meaning to general words or giving the concrete meaning to abstract words is not productive. And it is rarely witnessed that words of positive nuances are negatively used. It is considered that such cases are partly restricted in the spoken language or the jargon. Such phenomena may happen by the incomplete understanding of English words.

• Journal of the Korean BIBLIA Society for library and Information Science
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• v.18 no.2
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• pp.229-251
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• 2007

The change in information technology demands drastic change in digital library service. This study defines what a social semantic digital library should consist of and proposes a new architecture that incorporates core functions needed in designing a SSDL. The SSDL supports semantic information processing based on metadata and ontology and is an innovation system that allows SSDL users to participate in generating new knowledge by interacting with existing metadata and ontology structures. This study designed a SSDL model that consists of five horizontal and two vertical structures.

• 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.

• Korean Journal of Computational Design and Engineering
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• v.13 no.3
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• pp.163-174
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• 2008

In this paper, for integrating of data on car parts we model information of parts that PDM system manages. Ontology of car parts applies existing ontology mapping research to integrate into car ontology. We propose a method for semantic integration of PLM object of MEMPHIS based on the integrated ontology. Through our method, we introduce C# ontology model to apply existing C# applications with ontology. We also classify ontology integration into three through examples and explain them. While semantically integrating PLM objects based on the integrated ontology, we explain the need for change of PLM object type and describe the process of change for PLM object type by examples.