• Journal of the Institute of Electronics Engineers of Korea CI
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• v.37 no.3
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• pp.1-11
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• 2000

An example-based machine translation approach is a new paradigm for resolving various problems caused by the rules of conventional rule-based machine translation. But, in pure example-based machine translation, it is very hard to find similar examples matched with input sentences by using reasonable parallel corpus. This problem causes large overheads in the process of sentence generation. This paper proposes new method of English-Korean transfer using both patterns and examples. The patterns are composed of sentence patterns and phrase patterns. Meta parts of the patterns make the example-based machine translation more practical by raising the probability to find similar examples. The use of patterns and examples can reduce the ambiguities in source language analysis and give us a high quality of MT. And experimental results with a test corpus are discussed.

• Journal of Digital Contents Society
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• v.15 no.4
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• pp.559-568
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• 2014

Previous polarity classification using sentiment analysis utilizes a sentence rule by product reviews based rating points. It is difficult to be applied to blogs which have not rating of product reviews and is possible to fabricate product reviews by comment part-timers and managers who use web site so it is not easy to understand a product and store reviews which are reliability. Considering to these problems, if we analyze blogs which have personal and frank opinions and classify polarity, it is possible to understand rightly opinions for the product, store. This paper suggests that we extract high frequency vocabularies in blogs by several domains and choose topic words. Then we apply a technique of sentiment analysis and classify polarity about contents of blogs. To evaluate performances of sentiment analysis, we utilize the measurement index that use Precision, Recall, F-Score in an information retrieval field. In a result of evaluation, using suggested sentiment analysis is the better performances to classify polarity than previous techniques of using the sentence rule based product reviews.

• Journal of the Korean School Mathematics Society
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• v.20 no.2
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• pp.77-89
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• 2017

Although it is not necessary to have much mathematical knowledge in Major Courses of Animal Resources curriculums in agricultural high school, the function of mathematics class has a much effect on Major Courses. Therefore, we extracted the mathematics contents included in Major Courses of Animal Resources curriculums in agricultural high school, and also evaluated students' understanding according to the description method in textbooks of Major Courses. Furthermore, we analyzed students' preference about the description method in textbooks related to the Major Courses. As a result, it turns out that the level of mathematics contents of Animal Resources major curriculums does not break bounds of middle school level. Furthermore, many students are not able to solve the middle school level of problems. It is also shown that the most preferred description method in textbooks of Animal Resources major curriculums is the sentence-equation mixed type. In this study, we propose to reconstruct the mathematics contents with basic knowledge needed to complete the Major Courses in order that students can complete them more easily, and furthermore, to choose the description method in textbooks of Major Courses as sentence-equation mixed type and detailed explanation about terms should be included into the bargain.

• Journal of Korean Home Economics Education Association
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• v.12 no.3
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• pp.53-63
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• 2000

The purpose of this study was quantitative and qualitative contents analysis of food and nutrition section in middle school textbooks of home economics, physical education and science. As a quantitative approach numbers of sentence lines tables, figures, photos, activities, and exercises were counted. As a qualitative approach, types of explanations were categorized by 7 criteria, and commons and differences of the contents of those subjects were compared. The conclusions of this study were summarized as follows: 1) Contents of food and nutrition section were divided into nutrients. water. energy, food groups, and nutritional problems. When average sentence lines of each were compared, those of nutrients were the longest in all 3 subjects. 2) When compared the numbers of tables, figures, and photos in 3 subjects of textbooks, there were more figures in home economics and science, and more tables in physical education. 3) There were more activities and exercises in home economics an science than in physical education. 4) The D(sentences with table) or E type(sentences with figure) was adapted for the explanation of nutrients functions, recommended dietary allowance, food sources, food groups, eating habits, and weight control in home economics: nutritions functions and energy metabolism in physical education : and digestion, body constituents, energy metabolism, and detection of nutrients in science. 5) Contents about classification and functions of nutrients. food sources deficiency water, energy contents of nutrients and obesity were shown in all 3 subjects. Food groups and eating habits were explained in detail in home economics whereas digestion of nutrients in the digestive tracts were explained in detail in science. Recommended dietary allowance for Koreans and basic food groups revised in 1995 were presented in home economics, whereas those revised in 1989 were presented in physical education. To avoid confusion, recommended dietary allowance for Koreans and food groups presented in physical education tex should be updated.

• Journal of the Institute of Electronics Engineers of Korea CI
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• v.39 no.6
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• pp.11-23
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• 2002

Computational models up to now for Korean morphology have been linear in that it deal with only segmentation of morphemes rather than formation of the internal structure of a word. When integrating a linear computational model with syntax analysis, it requires an additional interface component between this model and the syntax to bind morphemes into sentence constituents. Furthermore the linear model is not semantically intuitive. In this paper, based on word-syntactical viewpoint, we propose an integrated computational model that deals with morpheme segmentation, formation of syntactic element (sentence constituent), and even internal structure of word. Formalism of two-level morphology is employed to cope with morpheme segmentation and alternation problems, and functional diacritics are proposed to incorporate categorial context into the two-level formalism. A modified GLR-based algorithm is also proposed to check syntactical constraint of morphemes.

• Journal of KIISE:Software and Applications
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• v.31 no.4
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• pp.505-515
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• 2004

In a newspaper, 5W1H information is the most fundamental and important element for writing and understanding articles. Focusing on such a relation between a newspaper article and the 5W1H, we propose a summarization method based on the activation degree of 5W1H. To overcome problems of the lead-based and the title-based methods, both of which are known to be the most effective in newspaper summarization, sufficient 5W1H information is extracted from both a title and a lead sentence. Moreover, for each sentence, its weight is computed by considering various factors, such as activation degree of 5W1H, the number of 5W1H categories, and its length and position. These factors make a great contribution to the selection of more important sentences, and thus to the improvement of readability of the summarized texts. In an experimental evaluation, the proposed method achieved a precision of 74.7% outperforming the lead-based method. In sum, our 5W1H approach was shown to be promising for automatic summarization of newspaper articles.

• Journal of KIISE
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• v.44 no.2
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• pp.163-170
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• 2017

Despite the rise of studies in spoken to sign language translation, low-resource problems of sign language corpus have been rarely addressed. As a first step towards translating from spoken to sign language, we addressed the problems arising from resource scarcity when translating spoken language to manual signals translation using statistical machine translation techniques. More specifically, we proposed three preprocessing methods: 1) paraphrase generation, which increases the size of the corpora, 2) lemmatization, which increases the frequency of each word in the corpora and the translatability of new input words in spoken language, and 3) elimination of function words that are not glossed into manual signals, which match the corresponding constituents of the bilingual sentence pairs. In our experiments, we used different types of English-American sign language parallel corpora. The experimental results showed that the system with each method and the combination of the methods improved the quality of manual signals translation, regardless of the type of the corpora.

• Education of Primary School Mathematics
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• v.26 no.2
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• pp.83-97
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• 2023

Nominalization is one of the grammatical metaphors that makes it easier to mathematize the target that needs to be converted into a formula, but it has the disadvantage of making problem understanding difficult due to complex and compressed sentence structures. To investigate how this nominalization affects students' problem-solving processes, an analysis was conducted on 233 third-grade elementary school students' problem solving of eight arithmetic word problems with or without nominalization. The analysis showed that the presence or absence of nominalization did not have a significant impact on their problem understanding and their ability to convert sentences to formulas. Although the students did not have any prior experience in nominalization, they restructured the sentences by using nominalization or agnation in the problem understanding stage. When the types of nominalization change, the rate of setting the formula correctly appeared high. Through this, the use of nominalization can be a pedagogical strategy for solving word problems and can be expected to help facilitate deeper understanding.

• ETRI Journal
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• v.40 no.2
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• pp.257-265
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• 2018

Pronouns are frequently dropped in Korean sentences, especially in text messages in the mobile phone environment. Restoring dropped pronouns can be a beneficial preprocessing task for machine translation, information extraction, spoken dialog systems, and many other applications. In this work, we address the problem of dropped pronoun recovery by resolving two simultaneous subtasks: detecting zero-pronoun sentences and determining the type of dropped pronouns. The problems are statistically modeled by encoding the sentence and classifying types of dropped pronouns using a recurrent neural network (RNN) architecture. Various RNN-based encoding architectures were investigated, and the stacked RNN was shown to be the best model for Korean zero-pronoun recovery. The proposed method does not require any manual features to be implemented; nevertheless, it shows good performance.

• Education of Primary School Mathematics
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• v.2 no.2
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• pp.85-102
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• 1998

Since textbooks for elementary school mathematics in accordance with the seventh curriculum are 'Class I' textbooks, which are used as one and only one textbooks throughout the country, the following aspects have been considered： In the legal aspect, the contents including the curriculum for mathematics asked of the Writing Committee by the Ministry of Education were reflected; in the aspect of theory of mathematics education, the textbooks are written in a way appropriate to theory of mathematics education; and in the aspect of application of reality, the textbooks are written to help improving mathematics education in classrooms. Therefore, the main frame of writing the textbooks is to make students feel proud enough to say "I have done mathematics", through helping students rationally solve problems surrounding them by themselves with their experiences and activities. In the above viewpoint the following sentence is reflected upon: "Hundred explanations are not equal to one manipulation activity."