• The KIPS Transactions:PartB
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• v.15B no.4
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• pp.375-382
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• 2008

A protein's subcellular localization is considered an essential part of the description of its associated biomolecular phenomena. As the volume of biomolecular reports has increased, there has been a great deal of research on text mining to detect protein subcellular localization information in documents. It has been argued that linguistic information, especially syntactic information, is useful for identifying the subcellular localizations of proteins of interest. However, previous systems for detecting protein subcellular localization information used only shallow syntactic parsers, and showed poor performance. Thus, there remains a need to use a full syntactic parser and to apply deep linguistic knowledge to the analysis of text for protein subcellular localization information. In addition, we have attempted to use semantic information from the WordNet thesaurus. To improve performance in detecting protein subcellular localization information, this paper proposes a three-step method based on a full syntactic dependency parser and WordNet thesaurus. In the first step, we constructed syntactic dependency paths from each protein to its location candidate, and then converted the syntactic dependency paths into dependency trees. In the second step, we retrieved root information of the syntactic dependency trees. In the final step, we extracted syn-semantic patterns of protein subtrees and location subtrees. From the root and subtree nodes, we extracted syntactic category and syntactic direction as syntactic information, and synset offset of the WordNet thesaurus as semantic information. According to the root information and syn-semantic patterns of subtrees from the training data, we extracted (protein, localization) pairs from the test sentences. Even with no biomolecular knowledge, our method showed reasonable performance in experimental results using Medline abstract data. Our proposed method gave an F-measure of 74.53% for training data and 58.90% for test data, significantly outperforming previous methods, by 12-25%.

• The KIPS Transactions:PartB
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• v.13B no.3 s.106
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• pp.345-352
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• 2006

The practical English-Korean machine translation system should be able to translate long sentences quickly and accurately. The intra-sentence segmentation method has been proposed and contributed to speeding up the syntactic analysis. This paper proposes the syntactic category prediction method using decision trees for getting accurate parsing results. In parsing with segmentation, the segment is separately parsed and combined to generate the sentence structure. The syntactic category prediction would facilitate to select more accurate analysis structures after the partial parsing. Thus, we could improve the parsing accuracy by the prediction. We construct features for predicting syntactic categories from the parsed corpus of Wall Street Journal and generate decision trees. In the experiments, we show the performance comparisons with the predictions by human-built rules, trigram probability and neural networks. Also, we present how much the category prediction would contribute to improving the translation quality.

• Annual Conference on Human and Language Technology
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• 2002.10e
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• pp.189-196
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• 2002

질의응답 시스템이 올바른 답변을 제시하기 위해서는 사용자의 의도를 정확하고 강건하게 파악하는 것이 매우 중요하다. 이러한 요구 사항을 만족시키기 위해서 본 논문에서는 실용적 질의응답 시스템을 위한 질의 유형 분류기를 제안한다. 제안된 질의 유형 분류기는 규칙 기반의 방법과 통계 기반의 방법을 접목시킨 하이브리드 방법을 사용한다. 제안된 방법을 사용함으로써 수동으로 규칙을 작성하는 시간을 줄일 수 있었고 정확률을 향상시킬 수 있었으며 안정성을 보장받을 수 있었다. 제안된 방법에 대한 실험에서 질의 유형을 분류하는데 86%의 정확률을 얻었다.

• Nuclear Engineering and Technology
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• v.53 no.3
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• pp.866-878
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• 2021

Procedures play a key role in ensuring safe operation at nuclear power plants (NPPs). Development and maintenance of a large number of procedures reflecting the best knowledge available in all relevant areas is a complex job. This paper introduces a newly developed methodology and the implemented software, called iExtractor, for the extraction of syntactic and semantic information from NPP procedures utilizing natural language processing (NLP)-based technologies. The steps of the iExtractor integrated with sets of rules and an ontology for NPPs are described in detail with examples. Case study results of the iExtractor applied to selected procedures of a U.S. commercial NPP are also introduced. It is shown that the iExtractor can provide overall comprehension of the analyzed procedures and indicate parts of procedures that need improvement. The rich information extracted from procedures could be further utilized as a basis for their enhanced management.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.15 no.4
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• pp.1409-1425
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• 2021

In wide-ranging information society, fast and easy access to information in language of one's choice is indispensable, which may be provided by using various multilingual Natural Language Processing (NLP) applications. Natural language text contains references among different language elements, called anaphoric links. Resolving anaphoric links is a key problem in NLP. Anaphora resolution is an essential part of NLP applications. Anaphoric links need to be properly interpreted for clear understanding of natural languages. For this purpose, a mechanism is desirable for the identification and resolution of these naturally occurring anaphoric links. In this paper, a framework based on Hobbs syntactic approach and a system developed by Lappin & Leass is proposed for resolution of reflexive anaphoric links, present in Urdu text documents. Generally, anaphora resolution process takes three main steps: identification of the anaphor, location of the candidate antecedent(s) and selection of the appropriate antecedent. The proposed framework is based on exploring the syntactic structure of reflexive anaphors to find out various features for constructing heuristic rules to develop an algorithm for resolving these anaphoric references. System takes Urdu text containing reflexive anaphors as input, and outputs Urdu text with resolved reflexive anaphoric links. Despite having scarcity of Urdu resources, our results are encouraging. The proposed framework can be utilized in multilingual NLP (m-NLP) applications.

• 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.

• Korean Journal of Cognitive Science
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• v.3 no.1
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• pp.41-60
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• 1991

Most of the PC users manipulate the computer by using a few commands which are familiar with them. However by using Hangul sentences instead of using DOS commands, the optimal commands can be generated and flexibility can be provided. For this purpose, the conversion method of the input sentence into DOS commands is studied by means of morphological analysis, syntactic analysis, semantic analysis, and conceptual analysis. Tabular parsing is used in morphological analysis. case grammar is used in syntactic and semantic analysis. Case grammar is used in syntactic and semantic analysis. The meaning of sentence is represeented by the semantic network, from which we can generate a sequence DOS commands.

• Proceedings of the KIEE Conference
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• 1987.07b
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• pp.1284-1287
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• 1987

A method of quantitative electrocardiogram analysis, based on concepts drawn from syntactic pattern recognition theories, is described. The algorithm can be used for removing the Interference noises and base line drift as a filter function, and for reducing the number of points representing the digitized ECG waveform. The Parsing is performed with simple finite state automata inferred by experiments and suitable to be updated during experiment execution. Two parameters are utilized for defining the noise and these make the algorithm flexible. The examples for testing the algorithm is real ECG waveforms with noise. Some experimental results lire presented.

• Language and Information
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• v.13 no.1
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• pp.39-56
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• 2009

This paper investigates ordering alternation phenomena in Korean using the dative construction data from Sejong Corpus of Modern Korean (Kim, 2000). The paper first shows that syntactic weight and information structure are distinct and independent factors that influence word order in Korean. Moreover, it reveals that heaviness and givenness compete each other and exert diverging effects on word order, which contrasts the converging effects of these factors shown in word orders of right-branching languages like English. The typological variation of syntactic weight effect poses interesting theoretical and empirical questions, which are discussed in relation to processing efficiency in ordering.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.5 no.4
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• pp.303-308
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• 2004

Natural language query is the best user interface for the users of information retrieval systems. This paper Proposes a retrieval system with expanded keyword from syntactically-analyzed structures of user's natural language query based on natural language processing technique. Through the steps combining or splitting the compound nouns based on syntactic tree traversal, and expanding the other-formed or shorten-formed keyword into multiple keyword, the system performance was enhanced up to 11.3% precision and 4.7% correctness.