• Title/Summary/Keyword: dependency relation

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An Analysis of Korean Dependency Relation by Homograph Disambiguation (동형이의어 분별에 의한 한국어 의존관계 분석)

  • Kim, Hong-Soon;Ock, Cheol-Young
    • KIPS Transactions on Software and Data Engineering
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    • v.3 no.6
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    • pp.219-230
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    • 2014
  • An analysis of dependency relation is a job that determines the governor and the dependent between words in sentence. The dependency relation of predicate is established by patterns and selectional restriction of subcategorization of the predicate. This paper proposes a method of analysis of Korean dependency relation using homograph predicate disambiguated in morphology analysis phase. The disambiguated homograph predicates has each different pattern. Especially reusing a stage transition training dictionary used during tagging POS and homograph, we propose a method of fixing the dependency relation of {noun+postposition, predicate}, and we analyze the accuracy and an effect of homograph for analysis of dependency relation. We used the Sejong Phrase Structured Corpus for experiment. We transformed the phrase structured corpus to dependency relation structure and tagged homograph. From the experiment, the accuracy of dependency relation by disambiguating homograph is 80.38%, the accuracy is increased by 0.42% compared with one of undisambiguated homograph. The Z-values in statistical hypothesis testing with significance level 1% is ${\mid}Z{\mid}=4.63{\geq}z_{0.01}=2.33$. So we can conclude that the homograph affects on analysis of dependency relation, and the stage transition training dictionary used in tagging POS and homograph affects 7.14% on the accuracy of dependency relation.

A Data Dependency Elimination Algorithm for Extracting Maximum Parallelism (최대 병렬성 추출을 위한 자료 종속성 제거 알고리즘)

  • 송월봉;박두순
    • Journal of KIISE:Software and Applications
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    • v.26 no.1
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    • pp.139-139
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    • 1999
  • In most application programs, loops usually comprise most of the computation in a program and the most important source of parallelism. When the data dependency relation is uniformin terms of distance, several compile time parallelization methods were introduced. On the otherhand,when the data dependency relation is non-uniform in distance, the compile time extraction ofparallelism is much complicated. In this paper, a general method the extracting parallelism in nestedloops is presented. This algorithm can be applicable where the dependency relation is both uniform andnon-uniform in distance. According to execution repeatedly the statements in nested loops, thealgorithm which effectively removes these kind of data dependencies is developed in order to presentthe total parallelization of nested loops.

Structural Disambiguation of Korean Adverbs Based on Correlative Relation and Morphological Context

  • Seo, Young-Ae;Park, Sang-Kyu;Choi, Key-Sun
    • ETRI Journal
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    • v.28 no.6
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    • pp.803-806
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    • 2006
  • This letter addresses a structural disambiguation method for Korean adverbs based on the correlative relation constraints between adverbs and modifiees, and the morphological context information of sentences. Using the proposed method, we improved the dependency parsing accuracy of adverbs from 79.2 to 89%. The experimental result shows that the proposed method is especially expert in parsing adverbs which can modify multiple word classes or have a long distance dependency relation to their modifiees.

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Analysis of Smoking Temptation, Nicotine Dependency, Perceived Health Status corresponding to Stage of Change in Smoking Cessation in Middle Aged Men (중년흡연남성의 금연단계에 따른 흡연유혹, 니코틴의존도)

  • Chang Sung-Ok;Park Chang-Seung
    • Journal of Korean Academy of Fundamentals of Nursing
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    • v.8 no.1
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    • pp.69-80
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    • 2001
  • This study was done to investigate the relation of smoking temptation, stage of change in smoking cessation, nicotine dependency and perceived health status in middle aged men. Convenience samples of 176 subjects who were either smoked or used to smoke, aged between 30 to 64, living in Seoul and Kyungi province area in Korea were selected for the study. The data was collected from December 1, 1999 to June 30, 2000. The research instrument were Stage of Change of Smoking Cessation Measure (DiClemente et al. 1991). Smoking Temptation Measure (Velicer, DiClemente, Rossi, Prochaska. 1990), Perceived Health Status Measure (McDowell & Newell, 1996), and Nicotine Dependency Scale (FTQ: Fagerstrom, 1978). The data were analyzed using the SAS Program. The result of the study are as follows : 1. The analysis of variance and multiple comparison showed that according to the stage of change, there were significant mean differences in the three sub-factors of smoking temptation; 'positive affect situation (F=12.64, p=.0001)', 'negative affect situation (F=16.01, p=.0001)', 'habitual craving situation (F=14.43, p=.0001)' and nicotine dependency (F=4.12, p=.0033) The mean score for smoking temptation for the subjects who were in the precontemplation stage outweighed the mean score for smoking temptation for subjects who were in the maintenance stage. 2. Through discriminant analysis, it was found that negative affect situation was the most influential variable of the smoking temptation sub-factors which can be used to discriminate stage of change. 3. The analysis of Pearson correlation coefficients showed that there was a significant positive relation between nicotine dependency and negative affect situation of smoking cessation((r=0.2182, p=0.0045) and a significant negative relation between nicotine dependency and perceived health status(r=-0.2115, p=0.0059).

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Prediction of Prosodic Boundaries Using Dependency Relation

  • Kim, Yeon-Jun;Oh, Yung-Hwan
    • The Journal of the Acoustical Society of Korea
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    • v.18 no.4E
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    • pp.26-30
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    • 1999
  • This paper introduces a prosodic phrasing method in Korean to improve the naturalness of speech synthesis, especially in text-to-speech conversion. In prosodic phrasing, it is necessary to understand the structure of a sentence through a language processing procedure, such as part-of-speech (POS) tagging and parsing, since syntactic structure correlates better with the prosodic structure of speech than with other factors. In this paper, the prosodic phrasing procedure is treated from two perspectives: dependency parsing and prosodic phrasing using dependency relations. This is appropriate for Ural-Altaic, since a prosodic boundary in speech usually concurs with a governor of dependency relation. From experimental results, using the proposed method achieved 12% improvement in prosody boundary prediction accuracy with a speech corpus consisting 300 sentences uttered by 3 speakers.

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Korean Dependency Relation Labeling Using Bidirectional LSTM CRFs Based on the Dependency Path and the Dependency Relation Label Distribution of Syllables (의존 경로와 음절단위 의존 관계명 분포 기반의 Bidirectional LSTM CRFs를 이용한 한국어 의존 관계명 레이블링)

  • An, Jaehyun;Lee, Hokyung;Ko, Youngjoong
    • 한국어정보학회:학술대회논문집
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    • 2016.10a
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    • pp.14-19
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    • 2016
  • 본 논문은 문장에서의 어절 간 의존관계가 성립될 때 의존소와 지배소가 어떠한 관계를 가지는지 의존 관계명을 부착하는 모델을 제안한다. 국내에서 한국어 의존구문분석에 관한 연구가 활발히 진행되고 있지만 의존 관계만을 결과로 제시하고 의존 관계명을 제공하지 않는 경우가 많았다. 따라서 본 논문에서는 의존경로(Dependency Path)와 음절의 의존 관계명 분포를 반영하는 음절 임베딩를 이용한 의존 관계명 부착모델을 제안한다. 문장에서 나올 수 있는 최적의 입력 열인 의존 경로(Dependency Path)를 순차 레이블링에서 좋은 성능을 나타내고 있는 bidirectional LSTM-CRFs의 입력 값으로 사용하여 의존 관계명을 결정한다. 제안된 기법은 자질에 대한 많은 노력 없이 의존 경로에 따라 어절 및 음절 단어표상(word embedding)만을 사용하여 순차적으로 의존 관계명을 부착한다. 의존 경로를 사용하지 않고 전체 문장의 어절 순서를 바탕으로 자질을 추출하여 CRFs로 분석한 기존 모델보다 의존 경로를 사용했을 때 4.1%p의 성능향상을 얻었으며, 의존 관계명 분포를 반영하는 음절 임베딩을 사용한 bidirectional LSTM-CRFs는 의존 관계명 부착에 최고의 성능인 96.01%(5.21%p 개선)를 내었다.

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Korean Dependency Relation Labeling Using Bidirectional LSTM CRFs Based on the Dependency Path and the Dependency Relation Label Distribution of Syllables (의존 경로와 음절단위 의존 관계명 분포 기반의 Bidirectional LSTM CRFs를 이용한 한국어 의존 관계명 레이블링)

  • An, Jaehyun;Lee, Hokyung;Ko, Youngjoong
    • Annual Conference on Human and Language Technology
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    • 2016.10a
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    • pp.14-19
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    • 2016
  • 본 논문은 문장에서의 어절 간 의존관계가 성립될 때 의존소와 지배소가 어떠한 관계를 가지는지 의존 관계명을 부착하는 모델을 제안한다. 국내에서 한국어 의존구문분석에 관한 연구가 활발히 진행되고 있지만 의존 관계만을 결과로 제시하고 의존 관계명을 제공하지 않는 경우가 많았다. 따라서 본 논문에서는 의존 경로(Dependency Path)와 음절의 의존 관계명 분포를 반영하는 음절 임베딩를 이용한 의존 관계명 부착 모델을 제안한다. 문장에서 나올 수 있는 최적의 입력 열인 의존 경로(Dependency Path)를 순차 레이블링에서 좋은 성능을 나타내고 있는 bidirectional LSTM-CRFs의 입력 값으로 사용하여 의존 관계명을 결정한다. 제안된 기법은 자질에 대한 많은 노력 없이 의존 경로에 따라 어절 및 음절 단어표상(word embedding)만을 사용하여 순차적으로 의존 관계명을 부착한다. 의존 경로를 사용하지 않고 전체 문장의 어절 순서를 바탕으로 자질을 추출하여 CRFs로 분석한 기존 모델보다 의존 경로를 사용했을 때 4.1%p의 성능향상을 얻었으며, 의존 관계명 분포를 반영하는 음절 임베딩을 사용한 bidirectional LSTM-CRFs는 의존 관계명 부착에 최고의 성능인 96.01%(5.21%p 개선)를 내었다.

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Analyzing dependency of Korean subordinate clauses using a composit kernel (복합 커널을 사용한 한국어 종속절의 의존관계 분석)

  • Kim, Sang-Soo;Park, Seong-Bae;Park, Se-Young;Lee, Sang-Jo
    • Korean Journal of Cognitive Science
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    • v.19 no.1
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    • pp.1-15
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    • 2008
  • Analyzing of dependency relation among clauses is one of the most critical parts in parsing Korean sentences because it generates severe ambiguities. To get successful results of analyzing dependency relation, this task has been the target of various machine learning methods including SVM. Especially, kernel methods are usually used to analyze dependency relation and it is reported that they show high performance. This paper proposes an expression and a composit kernel for dependency analysis of Korean clauses. The proposed expression adopts a composite kernel to obtain the similarity among clauses. The composite kernel consists of a parse tree kernel and a liner kernel. A parse tree kernel is used for treating structure information and a liner kernel is applied for using lexical information. the proposed expression is defined as three types. One is a expression of layers in clause, another is relation expression between clause and the other is an expression of inner clause. The experiment is processed by two steps that first is a relation expression between clauses and the second is a expression of inner clauses. The experimental results show that the proposed expression achieves 83.31% of accuracy.

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Automatic Acquisition of Paraphrases Using Bilingual Dependency Relations

  • Hwang, Young-Sook;Kim, Young-Kil
    • ETRI Journal
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    • v.30 no.1
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    • pp.155-157
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    • 2008
  • This letter introduces a new method to automatically acquire paraphrases using bilingual corpora. It utilizes the bilingual dependency relations obtained by projecting a monolingual dependency parse onto the other language's sentence based on statistical alignment techniques. Since the proposed paraphrasing method can clearly disambiguate the sense of the original phrases using the bilingual context of dependency relations, it would be possible to obtain interchangeable paraphrases under a given context. Through experiments with parallel corpora of Korean and English language pairs, we demonstrate that our method effectively extracts paraphrases with high precision, achieving success rates of 94.3% and 84.6%, respectively, for Korean and English.

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Biaffine Dependency Parser for Korean (Biaffine 한국어 의존파서)

  • Shadikhodjaev, Uygun;Min, Tae Hong;Youn, Junyoung;Lee, Jae Sung
    • Annual Conference on Human and Language Technology
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    • 2018.10a
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    • pp.678-681
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    • 2018
  • Dependency parsing is an important task in natural language processing whose results are used in many downstream tasks such as machine translation, information retrieval, relation extraction, question answering and many others. Most of the dependency parsing literature focuses on using end-to-end and sequence-to-sequence neural architectures as the core of the system. One such system, namely Biaffine dependency parser is explored in the current paper for effective dependency parsing of Korean language.

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