• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.55-65
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• 1998

This study was intended to suggest the desirable direction in the 7th national curriculum revision through the analysis of the elementary science textbooks in the 6th national curriculum. The analysis system was composed of three categories, (1)knowledge (2)inquiry process and (3)attitude. And knowledge was divided into fact, concept and rule. And inquiry process was divided into thirteen subcategories such as manipulating experimental apparatus, observing, measuring, recording data, classifying, interpreting/ predicting, determining relationship/ causal explanation, extrapolating/ interpolating, drawing conclusions/ formulating a generalization or model, evaluating, formulating a problem, generating a hypothesis and designing an experiment/ controlling variables. Each sentence in the textbooks was considered as an analyzing unit. The frequency and percentage of each category were counted and the ratios were calculated. The findings could be summarized as follows: 1. The content of the elementary science textbooks was composed of knowledge 10.3%, inquiry process 88.8%, attitude 0.8% respectively. 2. As increasing the grades, the ratio of knowledge showed high frequency, but that of attitude showed low frequency. 3. In All the grades, the ratio of observing was the highest in inquiry process. 4. In the domain of physics and chemistry, the manipulating experimental apparatus showed high frequency. In the domain of biology and earth science, the role of observing was emphasized.

• Journal of Korean Elementary Science Education
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• v.17 no.2
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• pp.45-53
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• 1998

This study was intended to suggest the desirable direction in the 7th national curriculum revision through the illustration analysis of the elementary science textbooks in the 6th national curriculum. The analysis system was composed of two categories, (1)the kind of illustrations (2)the .ole of illustrations The kind of illustrations was divided into five subcategories such as photograph, pictures, illustrations, cartoons and diagrams. And the role of illustrations was divided into four subcategories such as motive induction, guidance for experimentation, the presentation of data and the results of experimentation. Each sentence in the textbooks was considered as an analyzing units. The frequency and percentage of each category were counted and the rates were calculated. The findings could be summarized as follows: 1. The illustration in the primary science textbooks was mostly composed of photographs (87.1%). 2. The examination of the role of illustrations showed that the presentation of data was 46.2%, the guidance for experimentation 38.4%, the results of experimentation 8.6% and the motive induction 6.8% respectively. 3. In the domains of physical and chemical science, the role of guidance for experimentation was emphasized. But the biological and earth science domains showed high tendency of the presentation of data.

• Annual Conference on Human and Language Technology
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• 2018.10a
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• pp.652-657
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• 2018

With the rapid development of e-commerce, many customers can now express their opinion on various kinds of product at discussion groups, merchant sites, social networks, etc. Discerning a consensus opinion about a product sold online is difficult due to more and more reviews become available on the internet. Opinion Mining, also known as Sentiment analysis, is the task of automatically detecting and understanding the sentimental expressions about a product from customer textual reviews. Recently, researchers have proposed various approaches for evaluation in sentiment mining by applying several techniques for document, sentence and aspect level. Aspect-based sentiment analysis is getting widely interesting of researchers; however, more complex algorithms are needed to address this issue precisely with larger corpora. This paper introduces an approach of knowledge representation for the task of analyzing product aspect rating. We focus on how to form the nature of sentiment representation from textual opinion by utilizing the representation learning methods which include word embedding and compositional vector models. Our experiment is performed on a dataset of reviews from electronic domain and the obtained result show that the proposed system achieved outstanding methods in previous studies.

• The KIPS Transactions:PartB
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• v.12B no.3 s.99
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• pp.365-368
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• 2005

We propose a speech act analysis method for Korean dialogue using Support Vector Machines (SVM). We use a lexical form of a word, its part of speech (POS) tags, and bigrams of POS tags as sentence features and the contexts of the previous utterance as context features. We select informative features by Chi square statistics. After training SVM with the selected features, SVM classifiers determine the speech act of each utterance. In experiment, we acquired overall $90.54\%$ of accuracy with dialogue corpus for hotel reservation domain.

• The KIPS Transactions:PartB
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• v.14B no.2
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• pp.141-144
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• 2007

The longer the input sentences, the worse the syntactic parsing results, Therefore, a long sentence is first divided into several clauses and syntactic analysis for each clause is performed. Finally, all the analysis results art merged into one, In the merging process, it is difficult to determine the dependency among clauses, To handle such syntactic ambiguity among clauses, this paper proposes an SVM-based clause-dependency determination method. We extract various features from clauses, and analyze the effect of each feature on the performance. We also compare the performance of our proposed method with those of previous methods.

• Proceedings of the Korea Institute of Convergence Signal Processing
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• 2000.12a
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• pp.181-184
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• 2000

The new method of feature extraction is proposed, considering the statistic feature of human voice, unlike the conventional methods of voice extraction. PCA(principal Component Analysis) is applied to this new method. PCA removes the repeating of data after finding the axis direction which has the greatest variance in input dimension. Then the new method is applied to real voice recognition to assess performance. When results of the number recognition in this paper and the conventional Mel-Cepstrum of voice feature parameter are compared, there is 0.5% difference of recognition rate. Better recognition rate is expected than word or sentence recognition in that less convergence time than the conventional method in extracting voice feature. Also, better recognition tate is expected when the optimum vector is used by statistic feature of data.

• KIISE Transactions on Computing Practices
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• v.22 no.5
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• pp.240-245
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• 2016

In this study, comments on restaurants, movies, and mobile devices, as well as tweet messages regardless of specific domains were analyzed for sentimental information content. We proposed a system for extraction of objects (or aspects) and opinion words from each sentence and the subsequent evaluation. For the sentiment analysis, we conducted a comparative evaluation between the Structural SVM algorithm and the Latent Structural SVM. As a result, the latter showed better performance and was able to extract objects/aspects and opinion words using VP/NP analyzed by the dependency parser tree. Lastly, we also developed and evaluated the sentiment detector model for use in practical services.

• Proceedings of the Korean Information Science Society Conference
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• 1999.10b
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• pp.190-192
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• 1999

한국어는 용언이 의미적 제약을 통해 문장을 지배하는 SOV 구조의 언어이다. 또한, 조사나 어미와 같은 기능어의 발달은 물론 관형절은 내포하는 문장이 주류를 이룬다. 따라서 한국어의 구문분석은 부착에 따른 많은 구문 모호성이 발생하게 된다. 본 논문에서는 조건단일화 기반의 CFG문법을 기술하고 문형을 구문 제약으로 하여 구문모호성을 해결하는 방안을 제시한다. 문형은 한국어의 특성을 용언의 하위범주화에 맞게 재분류한 문장의 구조적 유형을 말한다. 본 논문에서 제안하는 문형은 동사와 형용사를 구분하여 39가지로 설정하였다. 이런 문형 정보를 이용하여 관형형 어미를 갖는 용언이 최대의 정보를 가지도록 함으로써 관형절에서 발생하는 부사 및 체언구 부착의 문제가 해결된다. 또한 문형은 이중주어나 이중 목적어 문장을 처리할 수가 있어 한국어에서 발생하는 많은 구문모호성을 해결할 수 있다.

• The Journal of Korean Medical History
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• v.15 no.2
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• pp.11-20
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• 2002

In "EuiMoonBubRyool" chapter 4, Yuchang criticized previous doctors since "damaged by wet in autumn" written in "Somun" must be corrected as "damaged by dry in autumn". The reason why the sentence must be corrected is that dry and damp are different atmosphere. He tried to explain with changes of season and the rapid pulse in autumn is said to be a contraindiction in "Naekyung" and it supports Autumn dry theory. He criticized previous doctors about many incorrect points of dry disease throu호 various aspects. Criticism on Dongwon's treatment, Dangye's medical theory and not having a treatment, and Mujungsoon's treatment and etc. are the examples. Symtoms and treatment of Dry disease that Yuchang commented helped in deepening the contents and widening the general understanding of the disease.

• Proceedings of the Acoustical Society of Korea Conference
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• 1994.06c
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• pp.111-115
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• 1994

In this paper, a variable time-scale modification using SOLA is proposed, which takes into consideration the different time-scaled characteristics of voiced and unvoiced speech. The conventional method performs time-scale modifiction at a uniform rate for all speech. For this purpose, voiced and unvoiced speech duration at various taling speeds were statistically analyzed. A clipping autocorrelation functio was applied to each analysis frame to detemine voiced and unvoiced speech to obtain respective variation rates. The results were used to perform variable time-scale modification to evaluate performance, a MOS test was conducted to compare the proposed voiced/unvoiced variable time-scale modification and the uniform SOLA method. Results indicate that the proposed method produces sentence quality superior to that of the conventional method.