• Journal of KIISE:Databases
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• v.35 no.2
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• pp.132-142
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• 2008

In biological domain, there exist a variety of protein analysis databases which have their own meaning toward the same target of protein. If we integrate these scattered heterogeneous data efficiently, we can obtain useful information which otherwise cannot be found from each original source. Reflecting the characteristics of biological data, each data source has its own syntax and semantics. If we describe these data through RDF(S) models, one of the Semantic Web standards, we can achieve not only syntactic but also semantic integration. In this paper, we propose a new concept of integration layer based on the RDF unified schema. As a conceptual model, we construct a unified schema focusing on the protein information; as a representational model, we propose a technique for the wrappers to aggregate necessary information from the relevant sources and dynamically generate RDF instances. Two example queries show that our integration layer succeeds in processing the integrated requests from users and displaying the appropriate results.

• The KIPS Transactions:PartB
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• v.13B no.1 s.104
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• pp.21-26
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• 2006

The semantic web is an emerging paradigm in the information retrieval and Web-based system. This paper deals with a Web change detection system which employs the semantic web and ontology. While existing Web change detection systems detect the syntactic change, the proposed system focuses on the detection of the semantic change. The system detects the change only when the web has semantic change. To achieve this, the system employs the domain-specific ontology (e.g., computer science professional person information in the paper). The Web pages regarding before and after change are converted according to the ontology. Then the comparison is performed. The experimental result shows the semantic-based change detection is more useful than the syntax-based change detection.

• 제어로봇시스템학회:학술대회논문집
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• 1992.10b
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• pp.74-78
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• 1992

This paper describes an intelligent system to automatic evaluation of eddy current(EC) signal for Inspection of steam generator(SG) tubes in nuclear power plant. Some features of the intelligent system design in the proposed system are : (1) separation of representation scheme ,or event capturing knowledge in EC signal and for structural inspection knowledge in SG tubes inspection; (2) each representation scheme is implemented in different methods, one is syntactic pattern grammar and the other is rule based production. This intelligent system also includes an data base system and an user interface system to support integration of the hybrid knowledge processing methods. The intelligent system based on the proposed concept is useful in simplifying the knowledge elicitation process of the rule based production system, and in increasing the performance in real time signal inspection application.

• The KIPS Transactions:PartD
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• v.9D no.6
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• pp.1091-1096
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• 2002

This paper presents the development of a protein interaction database. The developed system is characterized as follows. First, the proposed system not only maintains interaction data collected by an experiment, but also the genomic information of the protein data. Secondly, the system can extract details on interacting proteins through the developed wrappers. Thirdly, the system is based on wrapper-based system in order to extract the biologically meaningful data from various web sources and integrate them into a relational database. The system inherits a layered-modular architecture by introducing a wrapper-mediator approach in order to solve the syntactic and semantic heterogeneity among multiple data sources. Currently the system has wrapped the relevant data for about 40% of about 11,500 proteins on average from various accessible sources. A wrapper-mediator approach makes a protein interaction data comprehensive and useful with support of data interoperability and integration. The developing database will be useful for mining further knowledge and analysis of human life in proteomics studies.

• Journal of Digital Contents Society
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• v.17 no.3
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• pp.203-210
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• 2016

Korean is free of omission of sentence elements and modifying scope, so managing it on morphological analyzer is better than parser. In this paper, we propose functional expansion methods of the morphological analyzer to ease the burden of parsing. This method is a longest phrase matching method. When the series of several morpheme have one syntax category by processing of Unknown-words, Compound verbs, Compound nouns, Numbers and Symbols, our method combines them into a syntactic unit. And then, it is to treat by giving them a semantic features as syntax unit. The proposed morphological analysis method removes unnecessary morphological ambiguities and deceases results of morphological analysis, so improves accuracy of tagger and parser. By empirical results, we found that our method deceases 73.4% of Parsing tree and 52.4% of parsing time on average.

• The KIPS Transactions:PartD
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• v.18D no.5
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• pp.329-338
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• 2011

Terminology recognition system which is a preceding research for text mining, information extraction, information retrieval, semantic web, and question-answering has been intensively studied in limited range of domains, especially in bio-medical domain. We propose a domain independent terminology recognition system based on machine learning method using dictionary, syntactic features, and Web search results, since the previous works revealed limitation on applying their approaches to general domain because their resources were domain specific. We achieved F-score 80.8 and 6.5% improvement after comparing the proposed approach with the related approach, C-value, which has been widely used and is based on local domain frequencies. In the second experiment with various combinations of unithood features, the method combined with NGD(Normalized Google Distance) showed the best performance of 81.8 on F-score. We applied three machine learning methods such as Logistic regression, C4.5, and SVMs, and got the best score from the decision tree method, C4.5.

• The KIPS Transactions:PartB
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• v.14B no.3 s.113
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• pp.223-230
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• 2007

The purpose of developing an automated scoring system for English composition is to score the tests for writing English sentences and to give feedback on them without human's efforts. This paper presents an automated system to score English composition, whose input is a single sentence, not an essay. Dealing with a single sentence as an input has some advantages on comparing the input with the given answers by human teachers and giving detailed feedback to the test takers. The system has been developed and tested with the real test data collected through English tests given to the third grade students in junior high school. Two steps of the process are required to score a single sentence. The first process is analyzing the input sentence in order to detect possible errors, such as spelling errors, syntactic errors and so on. The second process is comparing the input sentence with the given answer to identify the differences as errors. The results produced by the system were then compared with those provided by human raters.

• The KIPS Transactions:PartB
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• v.16B no.2
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• pp.173-180
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• 2009

The purpose of developing an automated scoring system for English composition is to score English writing tests and to give diagnostic feedback to the test-takers without human's efforts. The system developed through our research detects grammatical errors of a single sentence on morphological, syntactic and semantic stages, respectively, and those errors are calculated into the final score. The error detecting stages are independent from one another, which causes duplicating the identical errors with different labels at different stages. These duplicated errors become a hindering factor to calculating an accurate score. This paper presents a solution to detecting the duplicated errors and improving an accuracy in calculating the final score by eliminating one of the errors.

• KIPS Transactions on Software and Data Engineering
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• v.5 no.3
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• pp.125-138
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• 2016

The service identification in service-oriented developments has been conducted by based on workflow, goals, scenarios, usecases, components, features, and patterns. However, the identification of service by semantic approach at the business value view was not detailed yet. In order to enhance accuracy of identifying business service, this paper proposes a method for identifying business service by analyzing syntax and semantics in XL-BPMN model. The business processes based on business scenario are identified, and they are designed in a XL-BPMN business process model. In this business process model, an unit business service is identified through binding closely related activities by the integrated analysis result of syntax patterns and properties-based semantic similarities between activities. The method through XL-BPMN model at upper business levels can identify the reusable unit business service with high accuracy and modularity. It also can accelerate more service-oriented developments by reusing identified services.

• Annual Conference on Human and Language Technology
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• 2000.10d
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• pp.405-410
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• 2000

본 연구에서는 기능적 자기공명영상을 이용하여 한글 문장의 의미와 통사 처리에 관한 뇌의 활성화 양상을 비교함으로써 한글문장 이해의 과정에 대한 신경해부학적 증거를 찾고자 하였다. 6명의 자원자를 대상으로 문장진위판단과제를 이용하여 활성화를 유도하였다. 1.5T 초전도 자기공명영상 장치에서 EPI로 BOLD 기법을 이용하여 기능적 영상을 얻었으며 영상 후 처리는 SPM99 분석 프로그램을 이용하였다. 의미관련 통사관련 문장 모두에서 좌 우 전두회(frontal gyrus) 영역에서 활성화되었다. 의미와 통사처리 영역을 구분하기 위하여 감산법을 적용한 결과, 의미처리는 좌반구의 중측두회(middle temporal gyrus) 영역에서, 통사처리는 우반구의 하전두회(BA44) 부위에서 더 많이 활성화되었다. 의미처리에서 더 우세한 성향을 띠는 부위로 밝혀진 중측두회 영역은 의미처리시에 활성화되는 영역으로 보고하는 기존의 연구와 일치하는 결과이다. 의미와 통사 문장처리시의 뇌 활성화 양상은 뇌의 여러 영역에서 중첩되어 있기는 하지만, 특정영역에서의 차이를 보이고 있으므로, 의미와 통사처리는 다른 기전(mechanism)에 의해서 일어남을 시사해 준다.