• The Journal of the Korea Contents Association
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• v.17 no.11
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• pp.389-397
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• 2017

Recently semantic web document is produced and added in repository in a cloud computing environment and requires an intelligent semantic agent for analytical classification of documents and information retrieval. The traditional methods of information retrieval uses keyword for query and delivers a document list returned by the search. Users carry a heavy workload for examination of contents because a former method of the information retrieval don't provide a lot of semantic similarity information. To solve these problems, we suggest a key word frequency and concept matching based semantic clustering model using hadoop and NoSQL to improve classification accuracy of the similarity. Implementation of our suggested technique in a cloud computing environment offers the ability to classify and discover similar document with improved accuracy of the classification. This suggested model is expected to be use in the semantic web retrieval system construction that can make it more flexible in retrieving proper document.

• The Journal of the Korea Contents Association
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• v.9 no.3
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• pp.1-8
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• 2009

This paper proposes a new document clustering system using fuzzy logic-based genetic algorithm (GA) and semantic vector expansion technology. It has been known in many GA papers that the success depends on two factors, the diversity of the population and the capability to convergence. We use the fuzzy logic-based operators to adaptively adjust the influence between these two factors. In traditional document clustering, the most popular and straightforward approach to represent the document is vector space model (VSM). However, this approach not only leads to a high dimensional feature space, but also ignores the semantic relationships between some important words, which would affect the accuracy of clustering. In this paper we use latent semantic analysis (LSA)to expand the documents to corresponding semantic vectors conceptually, rather than the individual terms. Meanwhile, the sizes of the vectors can be reduced drastically. We test our clustering algorithm on 20 news groups and Reuter collection data sets. The results show that our method outperforms the conventional GA in various document representation environments.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.274-284
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• 2008

XBRL is an XML-based language, actively used for diverse business reporting applications including financial reporting. It can be flexibly applied to each application by defining concepts and their relationships existing within the application. In these business reporting processes, it is very important for senders and receivers to validate the consistency and completeness of reporting contents in the syntatic and semantic levels. The basic method is to directly represent and validate the semantic constraints using application program codes. However, the method makes it difficult to represent, change, share semantic constraints. While XML constraint languages for XML documents such as XSLT and Schemantron support explicit representation and sharing of semantic constraints, they are limited in the efficiency and effectiveness of representing XBRL semantic constraints. This paper reviews XBRL formula, actively being discussed recently for standardization, and discusses the representation capability and limitations through a case analysis, which applies XBRL formula to business documents in the area of financial reporting.

• Korean Journal of Cognitive Science
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• v.15 no.1
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• pp.43-67
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• 2004

Using qualitative research methodology, this study has investigated the semantic features of 39 nouns, which are classified into the categories of grains, fruits and vegetables. A survey has been conducted with a substantial number of undergraduate students, who were asked to describe any semantic features they associated with the lexical items within the three categories. The analysis of the survey data shows that the concepts of examples of fruits are defined predominantly by intrinsic semantic features, while those of grains and vegetables are defined noticeably by extrinsic semantic features rather than intrinsic ones. Intrinsic semantic features are any properties inherent in an object itself and extrinsic semantic features are defined as any properties constructed by association with other objects or personal experiences in a certain situation. However, this study does not maintain that either intrinsic or extrinsic semantic features solely define the concepts of the examples of the three categories. Instead, it concludes that both kinds of semantic features are involved in the representation of the concepts of those vocabularies, with intrinsic features salient in the category of fruits and extrinsic features salient in the categories of gains and vegetables.

• English Language & Literature Teaching
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• v.7 no.1
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• pp.137-160
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• 2001

This paper is to suggest the way to improve EFL reading skill through semantic mapping by leveled group activities. Semantic mapping is a categorical structuring of information in graphic forms or diagrams. It can be used to activate and organize background knowledge on topics in classrooms. For small group activities, the class is divided into higher leveled groups and lower leveled groups of four members based on their grades. The teaching process has three stages: Pre-reading, while-reading, and post-reading. In the pre-reading stage, students discuss what they know about the topic. They map ideas with a brainstorming technique. In the while-reading stage, they read the text about the topic. While they are reading, they could ask some questions they might have and discuss the information in the text and categorize them with semantic mapping. In the post-reading stage, they discuss what they thought of the topic and add some information about the topic with semantic mapping. For the subjects of this study, third grade, middle school students were selected: 41 students for the experimental group and 35 students for the control group. The experimental period covered almost one semester from March to August, 2000. The results were as follows: 1) The students in the experimental group had higher scores in reading comprehension than those in the control group when semantic mapping was used; 2) The use of semantic mapping in reading comprehension was found to be much more effective in the higher leveled group than in the lower leveled group; 3) The results of questionnaires showed that many students became more interested and motivated in English, and semantic mapping helped them to participate positively in reading the English text. Thus, using semantic mapping by leveled group activities can be an effective alternative to traditional teaching methods for teachers who desire to improve reading skill in middle school students' English classes.

• The Research Journal of the Costume Culture
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• v.3 no.1
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• pp.17-25
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• 1995

The aim of thesis is to analyze dress phenomena, the semantic function and meaning of clothing were respectively on the basis of Semantics and Society by Geoffrey Leech and mentalistic semantics. To comprehend the actual clothing behaviour better, the pictures taken on the streets were used, including all kinds of the western-style and the traditional Korean costumes in Korea. The followings are the findings of the analysis. A in language, the semantic functions of the clothing are the informational, the expressive, the directive, the aesthetic, and the phatic functions. They communicate operating simultaneously. The clothing is the mentalistic semantics.

• 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.

• International Journal of Contents
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• v.10 no.4
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• pp.30-37
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• 2014

The current study was conducted to examine the temporal and spatial activation sequences related to morphosyntactic, semantic and orthographic-lexical sentences, focusing on the morphological-orthographic and lexical-semantic deviation processes in Korean language processing. The Event-related Potentials (ERPs) of 15 healthy students were adopted to explore the processing of head-final critical words in a sentential plausibility task. Specifically, it was examined whether the ERP-pattern to orthographic-lexical violation might show linear precedence over other processes, or the presence of additivity across combined processing components. For the morphosyntactic violation, fronto-central LAN followed by P600 was found, while semantic violation elicited N400, as expected. Activation of P600 was distributed in the left frontal and central sites, while N400 appeared even in frontal sites other than the centro-parietal areas. Most importantly, the orthographic-lexical violation process revealed by earlier N2 with fronto-central activity was shown to be complexes of morphological and semantic functions from the same critical word. The present study suggests that there is a linear precedence over the morphological deviation and its lexical semantic processing based on the immediate possibility of lexical information, followed by sentential semantics. Finally, late syntactic integration processes were completed, showing different topographic activation in order of importance of ongoing sentential information.

• The Journal of the Korea Contents Association
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• v.8 no.8
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• pp.9-18
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• 2008

Research is being made for users' convenient access to services such as personalized data and contents services. The use of information and the fusion of services in various devices and terminals suggest the necessity to know what personalization mechanism is used to provide high quality contents at a time and place desired by users. Existing mechanisms are not easy to be handled by other service providers because each service provider has different preference and personal information, and are very inconvenient because service users have to set up and manage by themselves. Thus, the present paper proposes a Semantic User Profiles Manager based on OSGi, middleware for the provision and extension of semantic services, in order to manage users' profiles dynamically regardless of service provider. In addition, this paper defines a personalized semantic profile that enables user profiling, ontological domain modeling and semantic reasoning. In order to test the validity of this paper, we implemented semantic profiles into a bundle running based on OSGi. When users enter the range of the service area and use various devices, the semantic service matches in correspondence with semantic user profiles. The proposed system can easily extend the matching of services to user profiles and matching between user profiles or between services.

• The Journal of the Korea Contents Association
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• v.10 no.6
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• pp.18-26
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• 2010

Many personalized services that provide users with adaptive information according to users' preferences have been researched and developed. Push services are especially expected to be more economic impact because push services satisfy user's potential needs even if the user does not require anything. In this paper, we propose Semantic Web approach in order to enhance the performance of push services. Our approach provides infrastructure to recommend contents based on semantic association by enabling information of contents and user preferences to be described on service-specific ontologies that reflect features of each service. In addition, our approach can recommend users with adaptive information based on information represented in our description model. Our approach enables information of contents and user preferences to be described with rich expressiveness, and it provides semantic interoperability.