• The Journal of Korean Institute of Communications and Information Sciences
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• v.5 no.1
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• pp.44-48
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• 1980

This paper proposes a method of the automatic recognition of the handprinted Hanguel patterns. A certain pattern oriented basic letters is normalized to the prototype Hanguel patten by the linking compansation and nomalization algorithm. Tree grammar is used in recognition process. Compared with the previous method. automata processing is simplified and the error is reduced by the new parsing method. This method shows the effectiveness for the constrained pattern. We expect that the new parsing method is very useful for the on-line pattern recognition.

• Journal of the Korean Society for Precision Engineering
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• v.20 no.3
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• pp.105-111
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• 2003

This paper presents an approach to automate process planning of press dies for manufacturing of car bodies. Considering that the press-dies used at the same press operations regardless of the panels they produce or the car models of which they produce panels have similar shapes except for the forming part of the dies, general approaches to recognize manufacturing features from CAD models are not necessary. Therefore, a hybrid approach is proposed combining feature-based design and feature-extraction approaches. The proposed method recognizes features by parsing the parameters extracted from CAD models and finds proper operations by querying the database by the recognized features. An internet-based process planning system is developed to demonstrate the proposed approach and to suggest a new paradigm of process planning system that utilizes an internet access to the CAD system.

• Journal of KIISE:Software and Applications
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• v.30 no.1_2
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• pp.81-92
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• 2003

Generalized LR parsing is one of the enhanced LR parsing methods so that it overcome the limit of one-way linear stack of the traditional LR parser using graph-structured stack, and it has been playing an important role of a firm starting point to generate other variations for NL parsing equipped with various mechanisms. In this paper, we propose a conditional Action Model that can solve the problems of conventional probabilistic GLR methods. Previous probabilistic GLR parsers have used relatively limited contextual information for disambiguation due to the high complexity of internal GLR stack. Our proposed model uses Surface Phrasal Types representing the structural characteristics of the parse for its additional contextual information, so that more specified structural preferences can be reflected into the parser. Experimental results show that our GLR parser with the proposed Conditional Action Model outperforms the previous methods by about 6-7% without any lexical information, and our model can utilize the rich stack information for syntactic disambiguation of probabilistic LR parser.

• Annual Conference on Human and Language Technology
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• 1994.11a
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• pp.426-433
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• 1994

본 논문에서는 트리의 점증적인 합성에 의하여 파싱을 진행시켜 나가는 파싱 방법을 소개하며 이의 한국어 파싱에의 응용을 살펴 본다. 이와 같은 트리 합성 파싱(tree combining parsing)을 지원하기 위한 문법인 트리 합성 문법(Tree Combining Grammar)을 소개한다. 우리는 먼저 문맥 자유 문법을 작성한 후 이로부터 자동적인 변환에 의하여 트리 합성 문법을 얻는 과정을 취한다. 따라서 트리 합성 파싱은 일종의 문맥 자유 파싱(context-free parsing)으로 볼 수 있으나 점증성(incremental), 하향성(top-down), 상향성(bottom-up), 유연성(flexible) 등과 같은 장점을 갖고 있다. 트리 합성 파싱의 유연성을 기반으로 하여 부분 자유 어순, 중심어 후행성과 같은 특성을 가진 한국어를 효과적으로 파싱할 수 있도록 트리 합성 파싱을 확장하는 방법을 살펴본다.

• Proceedings of the Korean Information Science Society Conference
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• 2003.04c
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• pp.513-515
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• 2003

본 논문에서는 코퍼스를 이용한 확률 의존문법 자동 생성 기술을 다룬다. 의존문법 생성을 위해 구성성분의 기능어들 간의 의존관계를 학습했던 기존 연구와는 달리. 한국어 구성성분은 내용어와 기능어의 결함 형태로 구성되고 임의 구성성룬 기능어와 임의 구성성분 내용어간의 의존관계가 의미가 있다는 사실을 반영한 의존문법 학습방법을 제안한다. KAIST의 트리 부착 코퍼스 31,086문장에서 추출한 30,600문장의 Tagged Corpus을 가지고 학습한 결과 초기문법을 64%까지 줄인 1.101 개의 의존문법을 획득했고. 실험문장 486문장을 Parsing한 결과 73.81%의 Parsing 정확도를 보였다.

• Korean Journal of Cognitive Science
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• v.4 no.1
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• pp.177-212
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• 1993

My research is based on the parser for ill-formed input by Mellish in a paper in ACL 27th meeting Proceedings. 1989. My system is composed of two parsers:WFCP and IFCP. When WFCP fails to give the parse tree for the input sentence, the sentence is identified as ill-formed and is parsed by IFCP for error detection and recovery at the syntactic level. My system is indendent of grammatical rules. It does not take into account semantic ill-formedness. My system uses a grammar composed of 25 context-free rules. My system consistes of two major parsing strategies:top-down expection and bottem-up satisfaction. With top-down expectation. rules are retrieved under the inference condition and expaned by inactive arcs. When doing bottom-up parsing. my parser used two modes:Left-Right parsing and Right-to-Left parsing. My system repairs errors sucessfully when the input contains an omitted word or an unknown word substitued for a valid word. Left- corner and right-corner errors are more easily detected and repaired than ill-formed senteces where the error is in teh middle. The deviance note. with repair details, is kept in new inactive arcs which are generated by the error correction procedure. The implementation of my system is quite different from Mellish's. When rules are invoked. my system invokes all rules with minimal inference. My bottom up parsing strategy uses Left-to-Right mode and Right-to-Left mode. My system is bottom-up-parsing-oriented like the chart parser. Errors are repaired in two ways:using top-down hypothesis, and using Need-Chart which keeps the information of expectation and complection of expanded goals by rules. To reduce the number of top-down cycles. all rules are invoked simultaneously and this invocation information is kept in Need-Chart. This idea will be extended for the implementation of multiple error recovery system.

• Korean Journal of Cognitive Science
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• v.6 no.2
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• pp.5-27
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• 1995

Based on the given data if three experiments that measured word-by-word reading times of the Korean relative-clause sentences,parsing strategies and performance structures in comprehending Korean sentences were suggested.First,results of the significantily longer reading time of nouns than verbs suggested that Korean parsing processing would be primarily occurred at nouns.Seond,four parsing strategies were proposed to explain increased reading times,working memory loads,and parallel function effects.Third,performance structures of sentence comprehension were constructed from the interword reading time differences.The proposed strategies and structures seem to account for the patterns of word-by-word reading times of the five types of the Korean relative-clause se various ideas for further experimentation were discussed.

• Journal of the Institute of Electronics and Information Engineers
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• v.51 no.8
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• pp.66-74
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• 2014

Recently a variety of study of Korean parsing system is carried out by many software engineers and linguists. The parsing system mainly uses the method of machine learning or symbol processing paradigm. But the parsing system using machine learning has long training time because the data of Korean sentence is very big. And the system shows the limited recognition rate because the data has self error. In this thesis we design system using feature module which can reduce training time and analyze the recognized rate each the number of training sentences and repetition times. The designed system uses the separated modules and sorted table for binary search. We use the refined 36,090 sentences which is extracted by Sejong Corpus. The training time is decreased about three hours and the comparison of recognized rate is the highest as 84.54% when 10,000 sentences is trained 50 times. When all training sentence(32,481) is trained 10 times, the recognition rate is 82.99%. As a result it is more efficient that the system is used the refined data and is repeated the training until it became the steady state.

• Proceedings of the Korean Information Science Society Conference
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• 2008.06c
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• pp.242-247
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• 2008

This paper discusses a design for Korean language parsing based on subcategorization. First, we discuss some important Korean grammar elements such as syntax category, josa, omi-conjugation, syntactic affix, dependent noun and also discuss subcategorization and expression patterns. Then, we show the basic structure of Korean language parsing process. The first stage scans the input sentence and processes article, noun phrase, numeral, josa, affix, dependent noun, adjective, omi-conjugation, adverb, auxiliary verb. The second stage deals with subcategorization patterns and expression patterns. The third stage processes the clauses and the fourth stage deals with SEA(Sentence Ending+Auxiliary).

• Journal of the Korean Institute of Telematics and Electronics
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• v.18 no.5
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• pp.15-21
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• 1981

This paper deals with the syntactic analysis algorithms of Korean sentence and system for machine translation. The parts of speech and constituients are syntactically analized at unified view-points and then an effective classification algorithm is proposed. The constituients which are applied an inverse movement transformation algorithm are processed with the concept of attribute. Syntactic analysis system is constructed to generate parsing table including the deep structure of sentence by lexicon proper to the combinational property of Korean and breadth-first searching method. The results obtained from the system program are shown as the parsing table of source sentences.