• Journal of the Institute of Electronics Engineers of Korea CI
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• v.38 no.3
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• pp.41-54
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• 2001

This paper propose an active rule and its semantic model integrating active rule system into temporal database. Most of previous works have been focused on condition action(CA) rule for temporal relations. However, proposed active rule model supports full SQL:3 trigger functionalitics including transition variable and table as well as tuple-level and statement-level active rules in E CA granularity. A bi-temporal concept of active rule and valid time event are also proposed newlv.

• Journal of the Korean Society for information Management
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• v.20 no.1
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• pp.341-371
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• 2003

The purpose of the study is to design the ontology-based Prescription Knowledge Management System of Oriental Medicine. The study was done with the premise that the effectiveness of the system can be improved by using ontological abstractional structure based on definition of concept, attribution and relations of words related to the specific area. The system is developed with Protege-2000 by using newly developed KPML(Korean Medicine Prescription Markup Language). The results of the study provide the model of Prescription Knowledge Management System and the possibility of implementing XML-based ontology system to the semantic web environment.

• Journal of Internet Computing and Services
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• v.8 no.2
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• pp.95-103
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• 2007

Many techniques have been proposed for mapping from XML to relations, but most techniques did not negotiate the semantics of XML data. The semantics is important to validate storage, query optimization, modification anomaly in process of schema design. Specially, functional dependencies are an important part of database theory, also it is basis of normalization for relational table in BCNF. This paper propose a new technique that reflect functional dependencies to store relation mapped from XML based on XML Schema. The technique can reduce storage redundancy and can keep up content and structure with constraint described by functional dependencies.

• Annual Conference on Human and Language Technology
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• 2008.10a
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• pp.35-41
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• 2008

이 논문은 각 문법 관계(grammatical relation)에서 선호되는 체언 어휘를 파악하고, 이 어휘들의 의미적 유형 및 그 위계를 파악하는 것이 목적이다. 이를 위해 80만 어절의 21세기 세종계획 구문분석 말뭉치에서 그 분포를 추출하고, 통계적 검증을 통해 각 문법 관계에서 선호되는 체언 어휘를 선별한다. 이 연구에서 관찰하는 문법 관계는 주어, 목적어, 용언수식어로 하며, 이들 문법 관계에서 선호되는 어휘 추출 대상 품사는 대명사, 고유명사, 일반명사로 한다. 한정성의 강도에 따라 주어 분포 경향이 나타나며, 이에 따라 대명사 > 고유명사 > 일반명사 순으로 주어 분포 경향이 나타난다. 그러나 일반적 예측과 다르게 한정성의 강도가 더 강한 것으로 알려진 대명사가 고유명사보다 목적어와 용언수식어에서 분포 경향이 더 강하여, 일반명사 > 대명사 > 고유명사의 순으로 분포 경향이 나타난다. 대명사, 고유명사, 일반명사는 공통적으로 주어에서는 사람 지시어, 목적어에서는 사물과 장소 지시어, 그리고 용언수식어에서는 시공간 표현이 선호되어 분포한다. 특히 대명사는 각 문법기능에서 인칭대명사의 경우 인칭에 따라, 그리고 지시대명사의 경우 원근칭에 따라 선호도의 차이를 보인다. 이러한 체언 어휘의 의미적 분포 특성은 문법 관계에 통사적 기능 외에도 의미적 경향이 반영된 것으로 고려될 수 있다.

• Journal of the Korean Society for information Management
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• v.1 no.1
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• pp.25-42
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• 1984

The intellectual organization of information for storage and retrieval is one of the problem areas of information science. But the most of the methods have been developed are based on the coordination of keywords by Boolean logic or traditional classification systems. It is necessary to include in indexing process not just concepts or keywords, but also to express explicitly the relationship between them. Farradane believed that such a system should be founded on the psychology of thinking and developed an outline structure for concept organization and a series of explicit relations. The system of relational operators provides nine symbols which enable the semantic relationship between any two concepts to be explicitly specified in a analet. With the addition of the permutations of such analets, formed according to simple rules, alphabetical arrangement of the first term provides a complete logical subject index. Relational indexing as the basis of an indexing language has the potential to offer improved retrieval performance.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.1
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• pp.86-93
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• 2008

The construction of ontology defines as complicated semantic relations needs precise and expert skills. For the well defined ontology in real applications, plenty of information of instances for ontology classes is very critical. In this study, crawling algorithm which extracts the fittest topic from the Web overflowing over by a great number of documents has been focused and developed. Proposed crawling algorithm made a progress to gather documents at high speed by extracting topic-specific Link using URL patterns. And topic fitness of Link block text has been represented by fuzzy sets which will improve a precision of the focused crawler.

• Journal of the Korea Society of Computer and Information
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• v.16 no.3
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• pp.189-201
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• 2011

In this paper, we design an ontology which provides interoperability by integrating typical metadata specifications and defines concepts and semantic relations between concepts that are used to describe metadata for learning objects in university courses. And we organize a hierarchical structured e-Learning system for efficient retrieval of learning objects on many local storages that use different specifications to describe metadata and propose a query processing method based on inferences. The proposed e-Learning system can provide more accurate and satisfactory retrieval service by using the designed ontology because both learning objects that be directly connected to user queries and deduced learning objects that be semantically connected to them are retrieved.

• Journal of Korea Game Society
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• v.20 no.3
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• pp.3-14
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• 2020

The purpose of this paper is to analyze the factors effecting users' satisfaction on game AI for early AI diffusion. For this purpose, we interviewed 20 users who had experiences playing Blade&Soul, made by NCsoft. Interview data had been analyzed through the Semantic Network Analysis program to identify key subject words and their relations. As a result, the paper has found keywords such as patterns, contents, variety, system, and getting new users as factors effecting users satisfaction on game AI.

• Proceedings of the Korean Institute of Landscape Architecture Conference
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• 2007.10b
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• pp.72-77
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• 2007

Civic participation in managing the work of a park is a natural experience, and urban culture has a role in forming and communicating ideas. However, when it comes to managing a copse, there is no clear scenic image. In this study, my intention was to determine a desirable scene involving a copse and suggest a target image for managing work from a scenic perspective. I selected 12 photographs and listed 10 pairs of adjectives that were judged to reflect the effect produced by the copse scene using the repertory grid development technique. In addition, I performed a scenic evaluation using the semantic differential(SD) method with each pair of adjectives. Factor analysis was performed based on questionnaire survey results, such that the scenic structure of the copse had a clear definition. In addition, the physical characteristics of the photographs were analyzed using Adobe Photoshop 6.0 and the correlations between the results of the questionnaire survey were understood using multiple regression analysis. A desirable scenic image of the copse became clear through this process and I was able to suggest various options of scenic images. Taking the aspects of urban culture into consideration, park improvement projects(including their planning stages) should be implemented by involving residents, which will lead to further development of park planning and maintenance theories and projects giving due consideration to residents' opinions.

• Journal of Information Science Theory and Practice
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• v.2 no.1
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• pp.6-21
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• 2014

This paper proposes a novel knowledge extraction system, TAKES (Two-step Approach for Knowledge Extraction System), which integrates advanced techniques from Information Retrieval (IR), Information Extraction (IE), and Natural Language Processing (NLP). In particular, TAKES adopts a novel keyphrase extraction-based query expansion technique to collect promising documents. It also uses a Conditional Random Field-based machine learning technique to extract important biological entities and relations. TAKES is applied to biological knowledge extraction, particularly retrieving promising documents that contain Protein-Protein Interaction (PPI) and extracting PPI pairs. TAKES consists of two major components: DocSpotter, which is used to query and retrieve promising documents for extraction, and a Conditional Random Field (CRF)-based entity extraction component known as FCRF. The present paper investigated research problems addressing the issues with a knowledge extraction system and conducted a series of experiments to test our hypotheses. The findings from the experiments are as follows: First, the author verified, using three different test collections to measure the performance of our query expansion technique, that DocSpotter is robust and highly accurate when compared to Okapi BM25 and SLIPPER. Second, the author verified that our relation extraction algorithm, FCRF, is highly accurate in terms of F-Measure compared to four other competitive extraction algorithms: Support Vector Machine, Maximum Entropy, Single POS HMM, and Rapier.