• Journal of the Korea Society of Computer and Information
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• v.19 no.1
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• pp.149-156
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• 2014

NGE(Nested Generalized Exemplar Method) can increase the performance of the noisy data at the same time, can reduce the size of the model. It is the optimal distance-based classification method using a matching rule. NGE cross or overlap hyperrectangles generated in the learning has been noted to inhibit the factors. In this paper, We propose the DHGen(Dominant Hyperrectangle Generation) algorithm which avoids the overlapping and the crossing between hyperrectangles, uses interval weights for mixed hyperrectangles to be splited based on the mutual information. The DHGen improves the classification performance and reduces the number of hyperrectangles by processing the training set in an incremental manner. The proposed DHGen has been successfully shown to exhibit comparable classification performance to k-NN and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.

• Journal of the Korean Institute of Intelligent Systems
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• v.13 no.3
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• pp.328-333
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• 2003

NGE (Nested Generalized Exemplars) proposed by Salzberg improved the storage requirement and classification rate of the Memory Based Reasoning. It constructs hyperrectangles during training and performs classification tasks. It worked not bad in many area, however, the major drawback of NGE is constructing hyperrectangles because its hyperrectangle is extended so as to cover the error data and the way of maintaining the feature weight vector. We proposed the OH (Optimizing Hyperrectangle) algorithm which use the feature weight vectors and the ED(Exemplar Densimeter) to optimize resulting Hyperrectangles. The proposed algorithm, as well as the EACH, required only approximately 40% of memory space that is needed in k-NN classifier, and showed a superior classification performance to the EACH. Also, by reducing the number of stored patterns, it showed excellent results in terms of classification when we compare it to the k-NN and the EACH.

• Journal of the Korean Institute of Intelligent Systems
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• v.18 no.4
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• pp.456-462
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• 2008

The classification is that a new data is classified into one of given classes and is one of the most generally used data mining techniques. Memory-Based Reasoning (MBR) is a reasoning method for classification problem. MBR simply keeps many patterns which are represented by original vector form of features in memory without rules for reasoning, and uses a distance function to classify a test pattern. If training patterns grows in MBR, as well as size of memory great the calculation amount for reasoning much have. NGE, FPA, and RPA methods are well-known MBR algorithms, which are proven to show satisfactory performance, but those have serious problems for memory usage and lengthy computation. In this paper, we propose DPA (Dynamic Partition Averaging) algorithm. it chooses partition points by calculating GINI-Index in the entire pattern space, and partitions the entire pattern space dynamically. If classes that are included to a partition are unique, it generates a representative pattern from partition, unless partitions relevant partitions repeatedly by same method. The proposed method has been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory and FPA, and RPA.

• The KIPS Transactions:PartB
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• v.13B no.2 s.105
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• pp.127-132
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• 2006

K-NN (k-Nearest Neighbors), which is a well-known instance-based learning algorithm, simply stores entire training patterns in memory, and uses a distance function to classify a test pattern. K-NN is proven to show satisfactory performance, but it is notorious formemory usage and lengthy computation. Various studies have been found in the literature in order to minimize memory usage and computation time, and NGE (Nested Generalized Exemplar) theory is one of them. In this paper, we propose RPA (Recursive Partition Averaging) and IRPA (Incremental RPA) which is an incremental version of RPA. RPA partitions the entire pattern space recursively, and generates representatives from each partition. Also, due to the fact that RPA is prone to produce excessive number of partitions as the number of features in a pattern increases, we present IRPA which reduces the number of representative patterns by processing the training set in an incremental manner. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1516-1522
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• 2007

We had proposed the FPA(Fixed Partition Averaging) method in order to improve the storage requirement and classification rate of the Memory Based Reasoning. The algorithm worked not bad in many area, but it lead to some overhead for memory usage and lengthy computation in the multi classes area. We propose an Repetitive FPA algorithm which repetitively partitioning pattern space in the multi classes area. Our proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory.

• Journal of Veterinary Clinics
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• v.25 no.5
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• pp.415-419
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• 2008

The purpose of this study was to determine clinical features of canine episcleritis and outcomes of therapy in Korea. The medical records of dogs with episcleritis presented at the Veterinary Medical Teaching Hospital of Seoul National University from January 2006 to December 2007 were reviewed. Episcleritis was diagnosed in 17 eyes of 12 dogs. The most frequently affected breed was Shih Tzu (n = 6). The median affected age was 5 years with a range from 3 years to 12 years. Simple episcleritis was identified in 8 dogs, nodular granulomatous episcleritis (NGE) in 3 dogs, and secondary episcleritis caused by panophthalmitis in a dog. The combination immunosuppressive therapy of topical corticosteroids, topical cyclosporine A, and intralesional injection of triamcinolone (4 mg) and gentamicin (4 mg) was performed. Most of the patients with episcleritis were resolved within 30 days following the therapy. Surgical excision was performed in 1 NGE case which was not responded to the medical therapy. Recurrence was observed in 4 dogs between 5 and 8 months after the first visit. It is considered that strong immunosuppressive therapy and periodic ocular examination are needed to control episcleritis.

• Proceedings of the Korea Information Processing Society Conference
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• 2005.11a
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• pp.477-480
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• 2005

메모리 기반 추론 기법에서 기억공간의 효율적 사용과 분류 시간을 줄이기 위한 다양한 방법들이 연구되고 있으며, NGE(Nested Generalized Exemplar) 이론을 예로 들 수 있다. 본 논문에서는 학습 패턴 집합으로부터 대표패턴을 생성하는 RPA(Recursive Partition Averaging) 기법과 점진적으로 대표패턴을 추출하는 IRPA(Incremental RPA) 기법을 제안한다.

• Journal of Navigation and Port Research
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• v.36 no.6
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• pp.465-474
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• 2012

Hamburg's development politics like "metropolis Hamburg - a growing city" demonstrates an important economic and demographic growth during 1997 to 2008. Beyond the positive factors with the idea of creative city, only selected class of people are involved in the city's active living, the others experience only gentrification. The G$\ddot{a}$ngeviertel, where the Hamburg's working class and dockworkers had lived, will be analysed as a historical important place of the gentrification since the end of the 19'century. This paper focuses on the actual Hamburg's movement of the initiatives "Komm in die G$\ddot{a}$nge" and " Right to the City", which took over the last 12 buildings of the G$\ddot{a}$ngeviertel. The G$\ddot{a}$ngeviertel Project, with the slogan "the city is neither a business nor a brand, but a community" could be an example of an alternative and sustainable solution for better living in the urban area of the Hamburg.

• Journal of IKEEE
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• v.12 no.1
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• pp.65-74
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• 2008

One of the popular methods used for pattern classification is the MBR (Memory-Based Reasoning) algorithm. Since it simply computes distances between a test pattern and training patterns or hyperplanes stored in memory, and then assigns the class of the nearest training pattern, it is notorious for memory usage and can't learn additional information from new data. In order to overcome this problem, we propose an incremental learning algorithm (iMPA). iMPA divides the entire pattern space into fixed number partitions, and generates representatives from each partition. Also, due to the fact that it can not learn additional information from new data, we present iMPA which can learn additional information from new data and not require access to the original data, used to train. Proposed methods have been successfully shown to exhibit comparable performance to k-NN with a lot less number of patterns and better result than EACH system which implements the NGE theory using benchmark data sets from UCI Machine Learning Repository.

• Koreanishche Zeitschrift fur Deutsche Sprachwissenschaft
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• v.3
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• pp.211-231
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• 2001

Es gibt verschiedene Auffassungen $\"{u}ber$ die Formulierung der Ableitung, wobei nur die Suffixbildung als Ableitung einerseits gelten soll oder andererseits die Suffix- und $Pr\"{a}fixbildung$ zusammen als Ableitung gelten sollen. Hier wird die zweite Auffassung als Ableitung angesehen und danach $geh\"{o}rt$ auch die Zirkumfixbildung zur Ableitung. Das einzige Zirkumfix, mit dem die Substantive abgeleitet werden, ist ge-+-e und dessen Suffix kann gegebenenfalls nicht explizit $ausgedr\"{u}ckt$ werden. Diese Substantivableitung wird zuerst nach der Wortart der Basis und dann nach der Funktion oder Bedeutung $folgenderma{\ss}en$ klassifiziert: 1. Deverbale Substantive: 1) Abstrakta: Gefecht, $Ger\"{a}usch,\;Gest\"{o}ber$ - Wiederholung bzw. Dauer: $Gedr\"{o}hn$, Gekreisch, $Get\"{o}se$ - Pejorative Bewertung: Gejammer, Gerede, Geschreibe 2) Resultat bzw.Produkt: $Gem\"{a}lde$, Gewebe, Gewucher 3) Person bzw. Sache: $Gedr\"{a}nge,\;Gew\"{a}chs,\;Ger\"{o}ll$ 4) Instrumentalia: $Gebl\"{a}se,\;Gefa{\ss}$, Gestell b) Denominale Substantive: Kollektiva: Gehim, $Gel\"{a}nde$, Gerippe