• Cross-Cultural Studies
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• v.36
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• pp.271-291
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• 2014

In this paper, we maintain that case makers '에e' and '에게ege', and '에서eseo' and '에게서egeseo' are not two separate morphemes but are simply allomorphs of the same morphemes respectively. When '에e' and '에게ege' are used as a dative marker, they show exactly the same semantic function and are in complementary distribution in relation to the semantic features of their preceding noun; that is, if the preceding noun is an animate noun, '에게ege' is used and '에e' is used if not. Also, '에게서egeseo' and '에서eseo' as ablative and locative case makers show exactly the same semantic function and show complementary distribution depending on whether the preceding noun is animate or non-animate. Therefore, we assume that these markers are semantically conditioned allomorphs.

• 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.

• Language and Information
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• v.14 no.2
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• pp.47-70
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• 2010

This study investigates the semantic and prosodic properties of the so-called contrastive topic. We posit two informational primitives, namely, topical feature [+-T] and focal feature [+-F], from which four different informational categories, i.e., [+T, +F], [+T, -F], [-T, +F], and [-T, -F], are yielded. It is proposed that the informational category of contrastive topic has focal property [+F] as well as topical property [+T]. Based on the semantic approach that regards the function of [+F] as identificational predication and that of [+T] as forming a semantic conditional clause, it is shown that the semantic function of contrastive topic, which is specified as [+T, +F], is the combination of these two functions, i.e., identificational predication in a semantic conditional clause. This is supported by a scrutinized exploration of the prosodic pattern of English contrastive topic.

• Korean Journal of Child Studies
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• v.18 no.2
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• pp.73-85
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• 1997

The purpose of the present study was to examine the role of semantic and syntactic knowledge in the first language acquisition of Korean classifiers. The elicited classifiers production test(EPT) was conducted to 105 children aged from 2 to 7. EPT consisted of 16 classifiers and two items for each classifier. 32 items were divided into 2 major semantic features: animacy and inanimacy. The semantic features of inanimacy were subcategorized into 3 features such as neutral, shape and function. The results revealed that; 1) children produced the correct structure of classification from the very early age with correct word order of the noun phrase showing early fundamental syntactic knowledge; 2) The earliest response pattern was to respond to all nouns in the same way using a neutral classifier showing no apparent semantic basis for their choice; 3) Children didn't show any preference for animate, shape, or function classifiers.

• Journal of the Korean Mathematical Society
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• v.36 no.3
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• pp.609-619
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• 1999

We give a mathematically rigorous description of the recently popular latent semantic indexing (LSI) method in text information retrieval theory. Also, a related problem of finding a document ranking function in linear relevance feedback is discussed.

• Proceedings of the Korean Society for Bioinformatics Conference
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• 2000.11a
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• pp.53-55
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• 2000

Xenie is the JAVA application software that integrates and represents 'gene to function'information of human gene. Xenie extracts data from several heterogeneous molecular biology databases and provides integrated information in human readable and machine usable way. We defined 7 semantic frame classes (Gene, Transcript, Polypeptide, Protein_complex, Isotype, Functional_object, and Cell) as a common schema for storing and integrating gene to function information and relationship. Each of 7 semantic frame classes has data fields that are supposed to store biological data like gene symbol, disease information, cofactors, and inhibitors, etc. By using these semantic classes, Xenie can show how many transcripts and polypeptide has been known and what the function of gene products is in General. In detail, Xenie provides functional information of given human gene in the fields of semantic objects that are storing integrated data from several databases (Brenda, GDB, Genecards, HGMD, HUGO, LocusLink, OMIM, PIR, and SWISS-PROT). Although Xenie provide fully readable form of XML document for human researchers, the main goal of Xenie system is providing integrated data for other bioinformatic application softwares. Technically, Xenie provides two kinds of output format. One is JAVA persistent object, the other is XML document, both of them have been known as the most favorite solution for data exchange. Additionally, UML designs of Xenie and DTD for 7 semantic frame classes are available for easy data binding to other bioinformatic application systems. Hopefully, Xenie's output can provide more detailed and integrated information in several bioinformatic systems like Gene chip, 2D gel, biopathway related systems. Furthermore, through data integration, Xenie can also make a way for other bioiformatic systems to ask 'function based query'that was originally impossible to be answered because of separatly stored data in heterogeneous databases.

• Journal of IKEEE
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• v.12 no.4
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• pp.217-224
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• 2008

This paper provides a framework for semantic correspondence of heterogeneous databases using self- organizing map. It solves the problem of overlapping between different databases due to their different schemas. Clustering technique using self-organizing maps (SOM) is tested and evaluated to assess its performance when using different kinds of data. Preprocessing of database is performed prior to clustering using edit distance algorithm, principal component analysis (PCA), and normalization function to identify the features necessary for clustering.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.12 no.8
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• pp.3790-3803
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• 2018

Content-based image retrieval is an approach used to query images based on their semantics. Semantic based retrieval has its application in all fields including medicine, space, computing etc. Semantically generated binary hash codes can improve content-based image retrieval. These semantic labels / binary hash codes can be generated from unlabeled data using convolutional autoencoders. Proposed approach uses semi-supervised deep hashing with semantic learning and binary code generation by minimizing the objective function. Convolutional autoencoders are basis to extract semantic features due to its property of image generation from low level semantic representations. These representations of images are more effective than simple feature extraction and can preserve better semantic information. Proposed activation and loss functions helped to minimize classification error and produce better hash codes. Most widely used datasets have been used for verification of this approach that outperforms the existing methods.

• Journal of information and communication convergence engineering
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• v.5 no.3
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• pp.249-253
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• 2007

The Research on the ICT(Information & Communication Technology) is proposed the category to IT839 strategy by Government. Government is driving to researching on technology about IT839 Strategy. By transforming this category and research information into Semantic Web environment, it is possible to search function utilizing knowledge base and information object by use of TBox and ABox. In this regard, this study proposes technology for generation of Semantic Web Document about ICT Research Information. The ontology is constructed by using category to IT839 Strategy. The features of framework proposed in this study is to have used a skill to directly map Ontology instance and in case of inability of direct mapping, proposed a skill to establish reliable Semantic Web Document by suggesting indirect mapping skill using mechanical study. In addition, it is possible to establish low cost/high quality Semantic Web Document about ICT research information.

• Journal of the Ergonomics Society of Korea
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• v.34 no.6
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• pp.563-581
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• 2015

Objective: This study was conducted to investigate the potential of sematic network analysis for design research. Background: As HCD (Human-Centered Design) was emphasized, lots of design research methodologies were developed and used in order to find user needs. However, it is still difficult to discover users' latent needs. This study suggests the semantic network analysis as a complementary means for design research, and proved its potential through the practical application, which compares multi-screen purchase and usage behaviors between America and China. Method: We conducted an in-depth interview with 32 consumers from USA and China, and analyzed interview texts through semantic network analysis. Cross cultural differences in purchase and usage behaviors were investigated, based on measuring centrality and community modularity of devices, functions, key buying factors and brands. Results: Americans use more services and functions in the multi-screen environment, compared to Chinese. As a device substitutes other devices, traditional boundaries of the devices are disappearing in the USA. Americans consider function to recall Apple, but Chinese consider function, design and brand to recall Apple, Sony and Samsung as an important brand at the time of their purchase. Conclusion: This study shows the potential of semantic network analysis for design research through the practical application. Semantic network analysis presents how the concepts regarding a theme are structured in the cognitive map of users with visual images and quantitative data. Therefore, it can complement the qualitative analysis of the existing design research. Application: As the design environment becomes more and more complicated like multi-screen environment, semantic network analysis, which is able to provide design insights in the intuitive and holistic perspective, will be acknowledged as an effective tool for further design research.