• The KIPS Transactions:PartB
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• v.14B no.7
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• pp.559-566
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• 2007

Subjective sentences express opinions, emotions, evaluations and other subjective ideas relevant to products or events. These expressions sometimes can be seen in only part of a sentence, thus extracting features from a full-sentence can degrade the performance of subjective-sentence-classification. This paper presents a method for improving the performance of a subjectivity classifier by combining two classifiers generated from the different representations of an input sentence. One representation is a sentimental phrase that represents an automatically identified subjective expression or objective expression and the other representation is a full-sentence. Each representation is used to extract modified n-grams that are composed of a word and its contextual words' polarity information. The best performance, 79.7% accuracy, 2.5% improvement, was obtained when the phrase-level classifier and the sentence-level classifier were merged.

• The Transactions of the Korea Information Processing Society
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• v.3 no.5
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• pp.1160-1169
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• 1996

In this study, an experiment of information retrieval using fuzzy connection matrix of keywords was conducted. A query for retrieval was constructed from each keyword and Boolean operator such as AND, OR, NOT. In a workstation environment, the performance of the fuzzy retrieval system was proved to be considerably effective than that of the system using the crisp set theory. And both recall ratio and precision ratio showed that the proposed technique would be a possible alternative in future information retrieval. Some special features of this experimental system were ; ranking the results in the order of connectivity, making the retrieval results correspond flexibly by changing the threshold value, trying to accord the retrieval process with the retrieval semantics by treating the averse-connectivity (fuzzy value) as a semantic approximation between kewords.

• Journal of KIISE:Software and Applications
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• v.26 no.10
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• pp.1247-1259
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• 1999

본 논문에서는 한국어 문장형성원리를 간결하게 제시할 수 있도록 X-바 이론의 중심어 개념을 도입한 한국어 자질기반 문법을 제안한다. 제안하는 문법은 어절에 관계없이 나타나는 한국어의 문법현상을 명확히 설명할 수 있도록 어절 대신 형태소를 기본단위로 한다. 그리고, 한국어의 구문범주가 지닌 의미정보와 기능정보를 자질을 이용하여 독립적으로 표현하며, 구문범주간의 결합관계를 바탕으로 하는 자질연산을 수행하여 문장을 분석한다. 또한, 한국어의 부분자유어순과 생략현상에 대해 견고하게 분석할 수 있도록 자질연산을 이진결합중심의 CNF(Chomsky Normal Form)로 제한한다. 이렇게 구성된 한국어 자질기반 문법은 규칙을 직관적이고도 간단하게 기술하며, 한국어의 다양한 문장들을 견고하게 분석한다. SERI Test Suites 97과 신문기사에서 746문장을 추출하여 실험한 결과 94%~99%의 적용율을 보였다.Abstract In this paper, we propose a Korean feature-based grammar(KFG) which adopts the X-bar theoretic notion of headedness for a precise representation of Korean syntactic structure. In order to explain various language phenomena in a given sentence, we use not the word but the morpheme as a constituent unit of KFG. We use features manifesting both the syntactic information and the semantic information of Korean syntactic categories, and feature operations based on the association relationship between two categories. In addition, we restrict feature operations to CNF(Chomsky Normal Form) binary form, which provides a robust representation for properties in Korean such as the frequent ellipsis and the partial free-order. The KFG is intuitive, simple, and versatile in representing most Korean sentences. The experimental result shows 94%~99% coverage on 746 sentences extracted from SERI Test Suites 97 and newspaper sentences.

• Korean Journal of Cognitive Science
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• v.14 no.2
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• pp.1-13
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• 2003

We introduce a way to generate morphologically and syntactically well-formed English sentences when building Korean to English bilingual dictionary for Machine Translation Systems. It has been proved that basic inflectional or structural descriptions for English sentences are by no means enough to generate proper English sentences because of traditional dictionary structures. Furthermore, much research has been focused only on how to disambiguate semantic ambiguities of words in a bilingual dictionary To take advantage of existing paperback Korean to English bilingual dictionary, its automatic conversion to an electronic version and methodologies to assign proper features to the descriptions for well-formed English sentences with minimum human effort have been proposed on the basis of the dictionary-specific structures. This approach was originally motivated for a glossary-based machine translation system, but it can be also applied to large scale dictionary work.

• Phonetics and Speech Sciences
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• v.4 no.4
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• pp.53-68
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• 2012

This study investigated the speech intelligibility of Korean-accented and native English focus speech for Korean and native English listeners. Three different types of focus in English, broad, narrow and contrastive, were naturally induced in semantically optimal dialogues. Seven high and seven low proficiency Korean speakers and seven native speakers participated in recording the stimuli with another native speaker. Fifteen listeners from each of Korean high & low proficiency and native groups judged audio signals of focus sentences. Results showed that Korean listeners were more accurate at identifying the focal prominence for Korean speakers' narrow focus speech than that of native speakers, and this suggests that the interlanguage speech intelligibility benefit-talker (ISIB-T) held true for narrow focus regardless of Korean speakers' and listeners' proficiency. However, Korean listeners did not outperform native listeners for Korean speakers' production of narrow focus, which did not support for the ISIB-listener (L). Broad and contrastive focus speech did not provide evidence for either the ISIB-T or ISIB-L. These findings are explained by the interlanguage shared by Korean speakers and listeners where they have established more L1-like common phonetic features and phonological representations. Once semantically and syntactically interpreted in a higher level processing in Korean narrow focus speech, the narrow focus was phonetically realized in a more intelligible way to Korean listeners due to the interlanguage. This may elicit ISIB. However, Korean speakers did not appear to make complete semantic/syntactic access to either broad or contrastive focus, which might lead to detrimental effects on lower level phonetic outputs in top-down processing. This is, therefore, attributed to the fact that Korean listeners did not take advantage over native listeners for Korean talkers and vice versa.

• Journal of Broadcast Engineering
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• v.4 no.2
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• pp.155-163
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• 1999

In this paper, we propose novel scene change detection and key frame selection techniques, which use two feature images, i.e., DC and edge images, extracted directly from MPEG compressed video. For fast edge image extraction. we suggest to utilize 5 lower AC coefficients of each DCT. Based on this scheme, we present another edge image extraction technique using AC prediction. Although the former is superior to the latter in terms of visual quality, both methods all can extract important edge features well. Simulation results indicate that scene changes such as cut. fades, and dissolves can be correctly detected by using the edge energy diagram obtained from edge images and histograms from DC images. In addition. we find that our edge images are comparable to those obtained in the spatial domain while keeping much lower computational cost. And based on HVS, a key frame of each scene can also be selected. In comparison with an existing method using optical flow. our scheme can select semantic key frames because we only use the above edge and DC images.

• The Mathematical Education
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• v.47 no.4
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• pp.519-543
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• 2008

The study has been conducted with 29 children from 4th to 6th grades to realize how they understand addition, subtraction, multiplication, and division of whole numbers, and how their understanding influences solving of one-step word problems. Children's understanding of operations was categorized into "adding" and "combination" for additions, "taking away" and "comparison" for subtractions, "equal groups," "rectangular arrange," "ratio," and "Cartesian product" for multiplications, and "sharing," "measuring," "comparison," "ratio," "multiplicative inverse," and "repeated subtraction" for divisions. Overall, additions were mostly understood additions as "adding"(86.2%), subtractions as "taking away"(86.2%), multiplications as "equal groups"(100%), and divisions as "sharing"(82.8%). This result consisted with the Fischbein's intuitive models except for additions. Most children tended to solve the word problems based on their conceptual structure of the four arithmetic operations. Even though their conceptual structure of arithmetic operations helps to better solve problems, this tendency resulted in wrong solutions when problem situations were not related to their conceptual structure. Children in the same category of understanding for each operations showed some common features while solving the word problems. As children's understanding of operations significantly influences their solutions to word problems, they needs to be exposed to many different problem situations of the four arithmetic operations. Furthermore, the focus of teaching needs to be the meaning of each operations rather than computational algorithm.

• Journal of the Korean Society of Clothing and Textiles
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• v.30 no.5 s.153
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• pp.699-710
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• 2006

The objective of this study was to identify the texture-related components of woven fabrics and to develop a multidimensional perceptual structure map to represent the tactile textures. Eighty subjects in clothing and tektite industries were selected for multivariate data on each fabric of 30 using the questionnaire with 9 pointed semantic differential scales of 20 texture-related adjectives. Data were analyzed by factor analysis, hierarchical cluster analysis, and multidimensional scaling(MDS) using SPSS statistical package. The results showed that the five factors were selected and composed of density/warmth-coolness, stiffness, extensibility, drapeability, and surface/slipperiness. As a result of hierarchical cluster analysis, 30 fabrics were grouped by four clusters; each cluster was named with density/warmth-coolness, surface/slipperiness, stiffness, and extensibility, respectively. By MDS, three dimensions of tactile texture were obtained and a 3-dimensional perceptual structure map was suggested. The three dimensions were named as surface/slipperiness, extensibility, and stiffness. We proposed a positioning perceptual map of fabrics related to texture naming system(TNS). To classify the textural features of the woven fabrics, hierarchical cluster analysis containing all the data variations, even though it includes the errors, may be more desirable than texture-related multidimensional data analysis based on factor loading values in respect of the effective variables reduction without losing the critical variations.

• Journal of Internet Computing and Services
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• v.20 no.6
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• pp.1-10
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• 2019

Object-based image matching algorithms have been widely used in the image processing and computer vision fields. A variety of applications based on image matching algorithms have been recently developed for object recognition, 3D modeling, video tracking, and biomedical informatics. One prominent example of image matching features is the Scale Invariant Feature Transform (SIFT) scheme. However many applications using the SIFT algorithm have implemented based on stand-alone basis, not client-server architecture. In this paper, We initially implemented based on client-server structure by using SIFT algorithms to identify and match objects in biomedical images to provide useful information to the user based on the recently released Mobile platform. The major methodological contribution of this work is leveraging the convenient user interface and ubiquitous Internet connection on Mobile device for interactive delineation, segmentation, representation, matching and retrieval of biomedical images. With these technologies, our paper showcased examples of performing reliable image matching from different views of an object in the applications of semantic image search for biomedical informatics.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.203-210
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• 2016

Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.