• KIPS Transactions on Software and Data Engineering
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• v.4 no.7
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• pp.283-290
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• 2015

In this paper, we propose a hybrid method for the recognition of answer types in the WiseQA system. The answer types are classified into two categories: the lexical answer type (LAT) and the semantic answer type (SAT). This paper proposes two models for the LAT detection. One is a rule-based model using question focuses. The other is a machine learning model based on sequence labeling. We also propose two models for the SAT classification. They are a machine learning model based on multiclass classification and a filtering-rule model based on the lexical answer type. The performance of the LAT detection and the SAT classification shows F1-score of 82.47% and precision of 77.13%, respectively. Compared with IBM Watson for the performance of the LAT, the precision is 1.0% lower and the recall is 7.4% higher.

• Journal of KIISE:Software and Applications
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• v.34 no.1
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• pp.18-29
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• 2007

In this paper we present a system that classifies brain MR images by using 2 level decision tree learning. There are two kinds of information that can be obtained from images. One is the low-level features such as size, color, texture, and contour that can be acquired directly from the raw images, and the other is the high-level features such as existence of certain object, spatial relations between different parts that must be obtained through the interpretation of segmented images. Learning and classification should be performed based on the high-level features to classify images according to their semantic meaning. The proposed system applies decision tree learning to each level separately, and the high-level features are synthesized from the results of low-level classification. The experimental results with a set of brain MR images with tumor are discussed. Several experimental results that show the effectiveness of the proposed system are also presented.

• Journal of the Computational Structural Engineering Institute of Korea
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• v.29 no.4
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• pp.335-345
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• 2016

It has problems to use the existing construction information classification system as the bridge breakdown structure due to lack of relationships between element classes. In this study, we proposed the bridge breakdown system for supplementation of above-mentioned classification system. The proposed system, for geometric information modeling, was based on international standards of methodology for structuring part families namely PLIB Part 42. In particular, the breakdown system, considering of the functional classification for the semantic information of the elements is included. In addition, we proposed a basic framework for actual modeling using bridge breakdown system and showed that it can be used in practice.

• Journal of the Korean Institute of Telematics and Electronics B
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• v.33B no.4
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• pp.183-190
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• 1996

The purpose of this paper is to show that the solutions of the problem for the anaphor ocured in korean senstence, by means of one-direction activated chart parsing leaded by a head. This is the phenomenon frequently occured in the conversation of natural language and the part necessarily required in the construction of natural language processing system for the practical use. To solve the problem of anaphor in the korean language, we have computerized definition and the management conditions necessary in the semantic classification between the anaphor and its antecedent and index are added in the feature structure in lexicon. To deal with anaphor in parser and algorithm is proposed to solve the problem for anaphor. The range of management of pareser is extended to solve the problem for anaphor of the indeclinable parts of speech in korean occured in all the sentences the parser HPSG developed previously manages.

• ETRI Journal
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• v.30 no.3
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• pp.432-440
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• 2008

In this paper, a user-friendly mobile photo album system and albuming functions to support it are introduced. Stand-alone implementation in a mobile device is considered. The main idea of user-friendly photo browsing for albuming functions is to enable users to organize and browse their photos along semantically meaningful axes of events, personal identities, and categories. Experimental results demonstrate that the proposed method would be sufficiently useful and efficient for browsing personal photos in mobile environment.

• Journal of the Korean Society of Clothing and Textiles
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• v.26 no.10
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• pp.1412-1423
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• 2002

The purpose of this study is to objectively explain the visual sensibility of clothing torture that satisfies the consumer's sensibility. The photo stimuli on clothing texture are divided into hard, soft transparent and brilliant. For the study of image 38 kinds of costume samples is used. The Study was measured by using Semantic Differential method. The subjects were 410 females in twenties. The data were analyzed by factor analysis, ANOVA, MDS and regression analysis. Data were analyzed by SPSS. The major findings of this research were as follows: 1. As a result of the factor analysis,5 factors of visual sensibility were consist of high qualities, touches, looks, lightness, and warmness or coolness.2. There were significant difference in visual sensibility based on classification of clothing texture.3. The clothing texture was classified as thin-full, flat-lumpy. 4. As a result of the regression analysis, preferences of consumers can be connected directly with buying behavior and satisfaction can be closely related with preferences and positive buying behavior.

• Proceedings of the Korean Society for Noise and Vibration Engineering Conference
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• 2006.11a
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• pp.671-674
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• 2006

Heavy-weight impact sounds generated by impact ball were classified according to the frequency characteristics on the equal loudness contours. Sound quality metrics such as Zwicker's loudness, sharpness, roughness of each classified impact sound were also measured. Loudness spectrum has been regarded as an indication of the characteristics difference of each classified impact sound. The adjectives in Korean expressing the sound quality characteristics of floor impact sounds were also investigated by adoptability and similarity tests. The group of the adjectives was used to evaluate the sound quality of floor impact sound by semantic differential test method.

• Journal of information and communication convergence engineering
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• v.9 no.3
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• pp.287-294
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• 2011

This paper proposes a search system using the topic maps that it extends XMDR into Knowledge based XMDR for solving of the problems of the heterogeneity of distributed data on a network and integrate data by an efficient way. The proposed system combined Topic Maps and the extended metadata registry effectively. The Topic Maps represent related knowledge and reasoning relationship by associations of topic. And the extended metadata registry standards and manages the metadata of the local systems through registration and certification on the distributed environment. We also proposed a meta layer, include the meta topic and meta association to achieve semantic classification grouping of topics and to define relationship between Topic Maps and extended metadata registry.

• Journal of Information Technology Services
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• v.17 no.2
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• pp.165-177
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• 2018

Recently, online commerces are becoming more common due to factors such as mobile technology development and smart device dissemination, and online review has a big influence on potential buyer's purchase decision. This study presents a set of analytical methodologies for understanding the meaning of customer reviews of products in online transaction. Using techniques currently developed in deep learning are implemented Hierarchical Attention Network for analyze meaning in online reviews. By using these techniques, we could solve time consuming pre-data analysis time problem and multiple topic problems. To this end, this study analyzes customer reviews of laptops sold in domestic online shopping malls. Our result successfully demonstrates over 90% classification accuracy. Therefore, this study classified the unstructured text data in the semantic analysis and confirmed the practical application possibility of the review analysis process.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.155-159
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• 2018

최근 화두가 되고있는 지능형 개인 비서 시스템에서 자연어 이해(NLU) 시스템은 중요한 구성요소이다. 자연어 이해 시스템은 사용자의 발화로부터 대화의 도메인(domain), 의도(intent), 의미적 슬롯(semantic slot)을 분류하는 역할을 한다. 하지만 자연어 이해 시스템을 학습하기 위해서는 많은 양의 라벨링 된 데이터를 필요로 하며 새로운 도메인으로 시스템을 확장할 때, 새롭게 데이터 라벨링을 진행해야 하는 한계점이 존재한다. 이를 해결하기 위해 본 연구는 적대 학습 방법을 이용하여 풍부한 양으로 구성된 기존(source) 도메인의 데이터부터 적은 양으로 라벨링 된 데이터로 구성된 대상(target) 도메인을 위한 슬롯 채우기(slot filling) 모델 학습 방법을 제안한다. 실험 결과 적대 학습을 적용할 경우, 적대 학습을 적용하지 않은 경우 보다 높은 f-1 score를 나타냄을 확인하였다.