• Journal of Information Management
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• v.41 no.2
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• pp.31-46
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• 2010

Now named-entity recognition(NER) as a part of information extraction has been used in the fields of information retrieval as well as question-answering systems. Unlike words, named-entities(NEs) are generated and changed steadily in documents on the Web, newspapers, and so on. The NE generation causes an unknown word problem and makes many application systems with NER difficult. In order to alleviate this problem, this paper proposes a new feature generation method for machine learning-based NER. In general features in machine learning-based NER are related with words, but entities in named-entity dictionaries are related to phrases. So the entities are not able to be directly used as features of the NER systems. This paper proposes an encoding scheme as a feature generation method which converts phrase entities into features of word units. Futhermore, due to this scheme, entities with semantic information in WordNet can be converted into features of the NER systems. Through our experiments we have shown that the performance is increased by about 6% of F1 score and the errors is reduced by about 38%.

• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.19 no.6
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• pp.197-202
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• 2019

XML has been established as a de facto standard for representing and exchanging documents, and has been widely used as a logical data model. Using XML as a logical database model, it requires a conceptual model for the semantics that XML has. However, the existing conceptual models, such as Entity Relationship models and UML, have been extended their concepts to express the specific characteristics of XML, but so far, there are no standard models. This paper compares the characteristics of the typical model of conceptual model of XML by Extended Entity Relationship model from the perspective of database field. For this, we propose the requirements that must be met for XML, and on the basis of these requirements, the approaches of each model are compared.

• Journal of Korea Multimedia Society
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• v.4 no.6
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• pp.543-553
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• 2001

In this paper, we proposed management strategy of medical image data in order to solve the problem in traditional medical images migration method. As management strategy of medical image data we proposed EAT(Expanded Average Transaction time) data migration method and data storing method based on temporal interrelation. In EAT data migration strategy, we define the dividing criterion which distinguish entity versions to be stored in each storage and also define entity versions to be stored in each storage. We defined degree of overlap and degree of difference for any two entity versions, and integrated those values and described method which place entity versions to storage. In order to compare the number of cluster references when we change rate of temporal queries, the number of cluster references of proposed method is smaller than that of traditional method.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.18 no.8
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• pp.91-97
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• 2019

A method for generating 3D solid models and drawings for a rotor in the steam turbine is proposed. One of the most important design steps is generating the drawing for manufacturing it. This step is a very routine and time-consuming job because each drawing is composed of several kinds of views and many dimensions. To achieve automation for this activity, rotor profiles are composed of 2D entity groups with attributes. Based on this, the improved design process is developed as follows. First, the rotor profiles can be selected by searching for 2D entity groups using the related attributes. Second, the profiles are connected sequentially so that an entire rotor profile is determined. The completed profile is used to generate 2D drawings automatically, especially views, dimensions, and 3D models. The proposed method is implemented using a commercial CAD/CAM system, Unigraphics, and API functions written in C-language and applied to the rotor of steam turbines. Some illustrative examples are provided to show the effectiveness of the proposed method.

• Journal of National Security and Military Science
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• s.1
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• pp.269-310
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• 2003

AS Extensible Markup Language(XML) is emerging as the data format of the Internet era, there are increasing needs to efficiently transform between database and XML documents. In this paper, we propose a schema transformation method from relational database to XML database. To transform the schema, we represent input schema as Entity-Relationship diagram. Entity-Relationship model translator scans the input Entity-Relationship diagram using BFS (breadth First Search) and translates the diagram into hierarchical structure model. The XML Schema generator produces XML Scema code using the transformed hierarchical structure model. The proposed method has a merit that having reusability facility of XML Schema property in comparison with existing researches.

• Proceedings of the Korean Society for Language and Information Conference
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• 2007.11a
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• pp.349-357
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• 2007

Named entities (NEs) are important in many Natural Language Processing (NLP) applications, and discovering NE-related relations in texts may be beneficial for these applications. This paper proposes a method to extract the ISA relation between a "named entity" and its category, and an IS-RELATED-TO relation between the category and its related object. Based on the pattern extraction algorithm "Person Category Extraction" (PCE), we extend it for solving our problem. Our experiments on Wall Street Journal (WSJ) corpus show promising results. We also demonstrate a possible application of these relations by utilizing them for semantic search.

• International Journal of Naval Architecture and Ocean Engineering
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• v.6 no.3
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• pp.598-625
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• 2014

To support the procedure for determining an optimal liquefaction cycle for FLNG FEED, an ontological modeling method which can automatically generate various alternative liquefaction cycles were carried out in this paper. General rules in combining equipment are extracted from existing onshore liquefaction cycles like C3MR and DMR cycle. A generic relational model which represents whole relations of the plant elements has all these rules, and it is expressed by using the system entity structure (SES), an ontological framework that hierarchically represents the elements of a system and their relationships. By using a process called pruning which reduces the SES to a candidate, various alternative relational models of the liquefaction cycles can be automatically generated. These alternatives were provided by XML-based formats, and they can be used for choosing an optimal liquefaction cycle on the basis of the assessments such as process simulation and reliability analysis.

• ETRI Journal
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• v.46 no.1
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• pp.59-70
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• 2024

We introduce a high-performance named entity recognition (NER) model for written and spoken language. To overcome challenges related to labeled data scarcity and domain shifts, we use transfer learning to leverage our previously developed KorBERT as the base model. We also adopt a meta-pseudo-label method using a teacher/student framework with labeled and unlabeled data. Our model presents two modifications. First, the student model is updated with an average loss from both human- and pseudo-labeled data. Second, the influence of noisy pseudo-labeled data is mitigated by considering feedback scores and updating the teacher model only when below a threshold (0.0005). We achieve the target NER performance in the spoken language domain and improve that in the written language domain by proposing a straightforward rollback method that reverts to the best model based on scarce human-labeled data. Further improvement is achieved by adjusting the label vector weights in the named entity dictionary.

• 제어로봇시스템학회:학술대회논문집
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• 1991.10a
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• pp.707-712
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• 1991

In machining a part in CAD/CAM system, it is required that the drawing information should be automatically generated, modified, deleted, and thus be used as an general information throughout the entire manufacturing process. This research addresses basic entities(point, line, circle, arc) for design feature and combination of this features, based on GT concepts, with minimum user's manual input. This paper deals with the generalization of operating system which can cover the s parts which appears in mechanical part handbook and the basic constitutional part of sold base. The system developed shows a strong application impact on automatic process planning system of medium - size injection sold companies.

• Annual Conference on Human and Language Technology
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• 2020.10a
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• pp.128-131
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• 2020

엔터티 링킹은 주어진 문서 상에서 엔터티가 내포된 부분에 어떤 엔터티가 연결되어야 하는 지를 판단하는 작업이다. 따라서, 이 과정에서 엔터티의 표상을 얻어내는 것이 엔터티 링킹의 성능에 큰 영향을 끼치게 된다. 이 논문에서는 RELIC을 통해 엔터티 임베딩을 얻어내고, 이를 엔터티 링킹에 적용시킨 결과 0.57%p의 성능 향상을 이루었다.