• Journal of Korea Multimedia Society
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• v.6 no.6
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• pp.1088-1099
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• 2003

The syntax-directed translation using semantic actions is frequently used in construction of compiler for text programming languages. it is very useful for the language designers to develop compiler back-end using a syntax structure of a source programming language. Due to the lack of the integrated representation method for a parse tree node and modeling method of syntax structures, it is very hard to construct compiler using syntax-directed translation in visual languages. In this Paper, we propose a visual language compiler generation method for constructing a visual languages compiler automatically, using syntax-directed translation. Our method uses the Picture Layout Grammar as a underlying grammar formalism. This grammar allows our approach to generate parser efficiently u sing And-Or-Waiting Graph and encapsulating syntax definition as one unit. Unlike other systems, we suggest separating the specification and the generation of semantic actions. Because of this, it provides a very efficient method for modification.

• 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.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.16 no.4
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• pp.2764-2769
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• 2015

In this paper, we present a Korean syntactic analysis system which can generate all possible syntactic trees in a given sentence. Therefore, the number of syntactic trees by this syntactic analysis system can be increased exponentially. To solve this problem, we suggest a segmentation method and maximum connected unit in a segmentation. Maximum connected unit is a combined unit which contains all morphemes in a segmentation. According to the input sentence, it is possible one or more maximum connected unit in a segmentation. We extract 516 sentences to experiment randomly from the text book of Korean middle school. We could reduce about 28% of the number of syntactic trees.

• Journal of Korea Society of Industrial Information Systems
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• v.9 no.3
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• pp.64-70
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• 2004

Korean and Japanese have same structure of sentences because they belong to same family of languages. So, The transfer driven machine translation is most efficient to translate each other. This paper introduce a method which creates a transfer dictionary for Token Based Transfer Driven Koran-Japanese Machine Translation(TB-TDMT). If the transfer dictionaries are created well, we get rid of useless effort for traditional parsing by performing shallow parsing. The semi-parser makes the dependency tree which has minimum information needed output generating module. We constructed the transfer dictionaries by using the corpus obtained from ETRI spoken language database. Our system was tested with 900 utterances which are collected from travel planning domain. The success-ratio of our system is $92\%$ on restricted testing environment and $81\%$ on unrestricted testing environment.

• The KIPS Transactions:PartB
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• v.9B no.6
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• pp.791-798
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• 2002

In this thesis. we present a new method for inducing a probabilistic dependency grammar (PDG) from text corpus. As words in Korean are composed of a set of more basic morphemes, there exist various dependency relations in a word. So, if the induction process does not take into account of these in-word dependency relations, the accuracy of the resulting grammar nay be poor. In comparison with previous PDG induction methods. the main difference of the proposed method lies in the fact that the method takes into account in-word dependency relations as well as inter-word dependency relations. To access the performance of the proposed method, we conducted an experiment using a manually-tagged corpus of 25,000 sentences which is complied by Korean Advanced Institute of Science and Technology (KAIST). The grammar induction produced 2,349 dependency rules. The parser with these dependency rules shoved 69.77% accuracy in terms of the number of correct dependency relations relative to the total number dependency relations for best-1 parse trees of sample sentences. The result shows that taking into account in-word dependency relations in the course of grammar induction results in a more accurate dependency grammar.

• Journal of Korea Society of Industrial Information Systems
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• v.4 no.4
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• pp.40-46
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• 1999

This paper introduce a Koran-Japanese machine translation system which is a module in the spoken language interpreting system It is implemented based on the TDMT(Transfre Driven Machine Translation). We define a new unit of translation so called TOKEN. The TOKEN-based translation method resolves nonstructural feature in Korean sentences and increases the quaity of translating results. In our system, we get rid of useless effort for traditional parsing by performing semi-parsing. The semi-parser makes the dependency tree which has minimum information needed generating module. We constructed the generation dictionaries by using the corpus obtained from ETRI spoken language database. Our system was tested with 600 utterances which is collected from travel planning domain The success-ratio of our system is 87% on restricted testing environment and 71% on unrestricted testing environment.

• KIISE Transactions on Computing Practices
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• v.21 no.4
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• pp.333-337
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• 2015

In this paper, we suggest a Coreference Resolution system for Korean using Mention Pair with SVM. The system introduced in this paper, also be able to extract Mention from document which is including automatically tagged name entity information, dependency trees and POS tags. We also built a corpus, including 214 documents with Coreference tags, referencing online news and Wikipedia for training the system and testing the system's performance. The corpus had 14 documents from online news, along with 200 question-and-answer documents from Wikipedia. When we tested the system by corpus, the performance of the system was extracted by MUC-F1 55.68%, B-cube-F1 57.19%, and CEAFE-F1 61.75%.

• Journal of KIISE
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• v.41 no.11
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• pp.992-1005
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• 2014

Coreference resolution finds all expressions that refer to the same entity in a document. Coreference resolution is important for information extraction, document classification, document summary, and question answering system. In this paper, we adapt Stanford's Multi-pass sieve system, the one of the best model of rule based coreference resolution to Korean. In this paper, all noun phrases are considered to mentions. Also, unlike Stanford's Multi-pass sieve system, the dependency parse tree is used for mention extraction, a Korean acronym list is built 'dynamically'. In addition, we propose a method that calculates weights by applying transitive properties of centers of the centering theory when refer Korean pronoun. The experiments show that our system obtains MUC 59.0%, $B_3$ 59.5%, Ceafe 63.5%, and CoNLL(Mean) 60.7%.