• Communications of Mathematical Education
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• v.37 no.4
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• pp.569-590
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• 2023

The purpose of this case study is to compare and analyze the covariational reasoning levels of two middle school students revealed in the process of solving and generalizing algebra word problems. A class was conducted with two middle school students who had not learned quadratic equations in school mathematics. During the retrospective analysis after the class was over, a noticeable difference between the two students was revealed in solving algebra word problems, including situations where speed changes. Accordingly, this study compared and analyzed the level of covariational reasoning revealed in the process of solving or generalizing algebra word problems including situations where speed is constant or changing, based on the theoretical framework proposed by Thompson & Carlson(2017). As a result, this study confirmed that students' covariational reasoning levels may be different even if the problem-solving methods and results of algebra word problems are similar, and the similarity of problem-solving revealed in the process of solving and generalizing algebra word problems was analyzed from a covariation perspective. This study suggests that in the teaching and learning algebra word problems, rather than focusing on finding solutions by quickly converting problem situations into equations, activities of finding changing quantities and representing the relationships between them in various ways.

• The KIPS Transactions:PartB
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• v.11B no.5
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• pp.563-572
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• 2004

Sentence ion is a simplification of a sentence preserving its communicative function. It accomplishes sentence revision and concept ion simultaneously. Sentence revision is a method that resolves the discrepancy between human's thoughts and its expressed semantic in sentences. Concept ion is an expression of general ideas acquired from the common elements of concepts. Sentence ion selects the main constituents of given sentences and describes the upper concepts of them with detecting their semantic information. This enables sen fence revision and concept ion simultaneously. In this paper, a syntactic parser LGPI+ and an ontology OfN are utilized for sentence ion. Sentence abstracter SABOT makes use of LGPI+ and OfN. SABOT processes the result of parsing and selects the candidate words for sentence ion. This paper computes the sentence recall of the main sentences and the topic hit ratio of the selected sentences with the text understanding system using sentence ion. The sources are 58 paragraphs in 23 stories. As a result of it, the sentence recall is about .54 ～ 72% and the topic hit ratio is about 76 ～ 86%. This paper verified that sentence ion enables sentence revision that can select the topic sentences of a given text efficiently and concept ion that can improve the depth of text understanding.

• Annual Conference on Human and Language Technology
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• 2004.10d
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• pp.251-258
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• 2004

본 연구는 연결어미가 글 이해와 기억에 미치는 영향을 조사하고, 연결어미의 효과와 글읽기 능력과는 어떤 관련성이 있는지를 조사하기 위해 실시되었다. 연결어미로는 인과 관계와 부가 관계를 나타내는 연결어미가 사용되었다. 앞뒤에 제시되는 두 문장의 국소적 응집성(Local coherence)을 형성하는데 연결어미가 도움을 준다면, 연결어미가 있는 경우에 문장을 이해하는 속도가 빨라지고 글 내용을 기억하는 데에도 도움을 줄 것으로 예측하였다. 만일에 글읽기 능력이 연결어미를 적절히 사용할 수 있는 능력에 의해서도 영향을 받는다면, 연결어미의 출현 여부와 읽기 능력간에 상호작용이 있을 것으로 예측하였다. 실험 1에서는 인과 관계 연결어미를 사용하여 문장 읽기 시간에 연결어미의 출현이 미치는 효과와 문장 회상에 미치는 효과를 조사하였다. 실험 결과, 인과 관계 연결어미는 뒤의 문장을 읽는데 촉진적인 효과를 주었으며, 이런 연결어미의 효과는 읽기 능력에 관계없이 일관된 촉진 효과를 나타냈다. 또한, 연결어미의 출현은 문장의 회상에 도움을 주었으며, 연결어미가 문장 회상에 미치는 효과는 읽기 능력의 상하에 관계없이 일관되게 나타났다. 실험 2에서는 부가 관계 연결어미가 문장 읽기 시간과 회상에 미치는 효과를 조사하였다. 실험 결과. 부가 관계 연결어미 역시 인과 관계 연결어미와 유사한 형태의 효과를 보였다. 실험 1과 실험 2의 결과는 인과 관계와 부가 관계 연결어미가 앞뒤 문장의 응집성 형성에 긍정적인 영향을 주고, 이런 연결어미의 글읽기에 대한 효과는 글읽기 능력에 관계없이 일정하다는 것을 시사한다.건이 복합 명사의 중심어 선택과 의미 결정에 재활용 될 수 있으며, 병렬말뭉치에 의해 반자동으로 구축되는 의미 대역 패턴을 사용하여 데이터 구축의 어려움을 개선하고자 한다. 및 산출 과정에 즉각적으로 활용될 수 있을 것이다. 또한, 이러한 정보들은 현재 구축중인 세종 전자사전에도 직접 반영되고 있다.teness)은 언화행위가 성공적이라는 것이다.[J. Searle] (7) 수로 쓰인 것(상수)(象數)과 시로 쓰인 것(의리)(義理)이 하나인 것은 그 나타난 것과 나타나지 않은 것들 사이에 어떠한 들도 없음을 말한다. [(성중영)(成中英)] (8) 공통의 규범의 공통성 속에 규범적인 측면이 벌써 있다. 공통성에서 개인적이 아닌 공적인 규범으로의 전이는 규범, 가치, 규칙, 과정, 제도로의 전이라고 본다. [C. Morrison] (9) 우리의 언어사용에 신비적인 요소를 부인할 수가 없다. 넓은 의미의 발화의미(utterance meaning) 속에 신비적인 요소나 애정표시도 수용된다. 의미분석은 지금 한글을 연구하고, 그 결과에 의존하여서 우리의 실제의 생활에 사용하는 $\ulcorner$한국어사전$\lrcorner$ 등을 만드는 과정에서, 어떤 의미에서 실험되었다고 말할 수가 있는 언어과학의 연구의 결과에 의존하여서 수행되는 철학적인 작업이다. 여기에서는 하나의 철학적인 연구의 시작으로 받아들여지는 이 의미분석의 문제를 반성하여 본다.반인과 다르다는 것이 밝혀졌다. 이 결과가 옳다면 한국의 심성 어휘집은 어절 문맥에 따라서 어간이나 어근 또는 활용형 그 자체로 이루어져

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2022.10a
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• pp.267-268
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• 2022

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Big data is usually in the form of sentences, and morphological analysis or understanding of the sentences is required. Accordingly, NLP, a technique for analyzing natural language, can understand the relationship of words and sentences. In this paper, we study the advantages and disadvantages of Transformers and Reformers, which are techniques that complement the disadvantages of RNN, which is a time series approach to big data.

• Annual Conference on Human and Language Technology
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• 2003.10d
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• pp.219-226
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• 2003

한국 수화는 한국어에 대한 기본적인 유사성을 가지고 있지만, 교착어이자 청각-음성 체계 언어인 한국어와는 달리 고립어이자 시각-운동 체계 언어로서의 특성을 동시에 나타내고 있다. 그러므로 텍스트 형태의 한국어 문장으로부터 수화를 자동 생성하기 위해서는 한국어를 위해 미리 정의된 문법에 수화 표현을 무리하게 연계시키려고 하기 보다, 수화 고유의 의미 전달 체계를 분석하고 활용하여야 할 필요가 있다. 본 논문에서는 수화 표현상의 언어학적 특징을 재현 생략 변형 이동의 네 가지로 구분하여 분석하고 결합범주문법을 이용한 이 같은 형상의 처리 방법 및 구현 방안에 대하여 논의한다.

• The Journal of the Acoustical Society of Korea
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• v.28 no.1
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• pp.61-69
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• 2009

This paper presents an improved method measuring inter-utterance similarity in an example-based dialogue system, which searches the most similar utterance in a dialogue database to generate a response to a given user utterance. Unlike general inter-sentence similarity measures, the inter-utterance similarity measure for example-based dialogue system should consider not only word distribution but also various linguistic features, such as affirmation/negation, tense, modality, sentence type, which affects the natural conversation. However, previous approaches do not sufficiently reflect these features. This paper proposes a new utterance similarity measure by analyzing and reflecting various linguistic features to improve performance in accuracy. Also, by considering substitutability of the features, the proposed method can utilize limited number of examples. Experimental results show that the proposed method achieves 10%p improvement in accuracy compared to the previous method.

• School Mathematics
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• v.9 no.1
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• pp.141-160
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• 2007

The purpose of this paper was to evaluate how students apply prior knowledge or experience in solving algebra word problems from the chain of signification-based perspective. Three middle school students were evaluated in this case study. The results showed that the subjects formed similarities in the process of applying knowledge needed for solving a problem. The student A and C used semi-open-end formulas and closed formulas as solutions. They then formed concrete shape for each solution using the chain of signification that was applied for solution by forming procedural similarity. At this time, the chain of signification could be the combination of numbers, words, and pictures (such as diagrams or graphs) or just numbers or words. On the other hand, the student C who recognized closed formulas and her own rule as a solution method could not formulate completely procedural similarity due to many errors arising from number information. Nonetheless, all of the subjects showed something in common in the process of coming up with a algorithm that was semi-open-end formula or closed formula.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.27 no.1
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• pp.41-46
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• 2023

Recently, big data analysis can use various techniques according to the development of machine learning. Big data collected in reality lacks an automated refining technique for the same or similar terms based on semantic analysis of the relationship between words. Since most of the big data is described in general sentences, it is difficult to understand the meaning and terms of the sentences. To solve these problems, it is necessary to understand the morphological analysis and meaning of sentences. Accordingly, NLP, a technique for analyzing natural language, can understand the word's relationship and sentences. Among the NLP techniques, the transformer has been proposed as a way to solve the disadvantages of RNN by using self-attention composed of an encoder-decoder structure of seq2seq. In this paper, transformers are used as a way to form associations between words in order to understand the words and phrases of sentences extracted from big data.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.1
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• pp.21-28
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• 2016

The performance of an English-Korean machine translation system depends heavily on its English parser. The parser in this paper is a part of the rule-based English-Korean MT system, which includes many syntactic rules and performs the chart-based parsing. The parser generates too many structures due to many syntactic rules, so much time and memory are required. The rule-based parser has difficulty in analyzing and translating the long sentences including the commas because they cause high parsing complexity. In this paper, we propose the 3-phase parsing method with sentence segmentation to efficiently translate the long sentences appearing in usual. Each phase of the syntactic analysis applies its own independent syntactic rules in order to reduce parsing complexity. For the purpose, we classify the syntactic rules into 3 classes and design the 3-phase parsing algorithm. Especially, the syntactic rules in the 3rd class are for the sentence structures composed with commas. We present the automatic rule acquisition method for 3rd class rules from the syntactic analysis of the corpus, with which we aim to continuously improve the coverage of the parsing. The experimental results shows that the proposed 3-phase parsing method is superior to the prior parsing method using only intra-sentence segmentation in terms of the parsing speed/memory efficiency with keeping the translation quality.

• The KIPS Transactions:PartB
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• v.11B no.6
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• pp.743-748
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• 2004

In this paper, we propose a probabilistic Korean parsing model using a syntactic feature, a functional feature, a content feature, and a site feature of a syntactic object for effective syntactic disambiguation. It restricts grammar rules to binary-oriented form to deal with Korean properties such as variable word order and constituent ellipsis. In experiments, we analyze the parsing performance of each feature combination. Experimental results show that the combination of different features is preferred to the combination of similar features. Besides, it is remarkable that the function feature is more useful than the combination of the content feature and the size feature.