• Journal of applied mathematics & informatics
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• v.12 no.1_2
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• pp.143-154
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• 2003

A finite group G is called (l, m, n)-generated, if it is a quotient group of the triangle group T(l, m, n) = 〈$\chi$, y, z│$\chi$$\^$l/ = y$\^$m/ = z$^n$ = $\chi$yz = 1〉. In [19], the question of finding all triples (l, m, n) such that non-abelian finite simple group are (l, m, n)-generated was posed. In this paper we partially answer this question for the sporadic group Ru. In fact, we prove that if p, q and r are prime divisors of │Ru│, where p < q < r and$.$(p, q) $\neq$ (2, 3), then Ru is (p, q, r)-generated.

• Journal for History of Mathematics
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• v.18 no.3
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• pp.25-38
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• 2005

We briefly survey the history of Chinese mathematics which concerns the resolution of right triangles. And we analyse the problems Yucigugosulyodohae(劉氏勾股述要圖解) which is the mathematical book of Chosun Dynasty and contains the 224 problems about right triangles only. Among them, 210 problems are for resolution of right triangles. We also present the methods for generating the Pythagorean triples and constructing polynomial equations in Yucigugosulyodohae which are needed for resolving right triangles.

• Journal of applied mathematics & informatics
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• v.23 no.1_2
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• pp.257-268
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• 2007

An oriented graph is a digraph with no symmetric pairs of directed arcs and without loops. The score of a vertex $v_i$ in an oriented graph D is $a_{v_i}\;(or\;simply\;a_i)=n-1+d_{v_i}^+-d_{v_i}^-,\;where\; d_{v_i}^+\;and\;d_{v_i}^-$ are the outdegree and indegree, respectively, of $v_i$ and n is the number of vertices in D. In this paper, we give a new proof of Avery's theorem and obtain some stronger inequalities for scores in oriented graphs. We also characterize strongly transitive oriented graphs.

• Journal of the Korea Society of Computer and Information
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• v.22 no.6
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• pp.69-77
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• 2017

The information related to legislation is massive, and it takes much time and effort to manually build the legislation ontology. Thus, studies on machine-based automated building methods are underway. However, the studies to automatically construct such systems focus on using TBox construction, and those based on automated ABox construction, which corresponds to instances, theoretical systems and data building cases, has not yet been sufficiently developed. Therefore, this paper suggests using a semi-automatic ABox construction method based on sentence patterns to automatically build the ontology for the legislation of the Republic of Korea. Precision and Recall experiments were conducted to further discuss the performance of the suggested method. These experiments provide a comparison between the manual classification, and the triples built by the machines of the legal information by assessing the corresponding numerical values.

• Journal of the Korean Mathematical Society
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• v.41 no.1
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• pp.107-130
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• 2004

A $JB^{*}-triple$ is a Banach space A on which the group Aut(B) of biholomorphic automorphisms acts transitively on the open unit ball B of A. In this case, a triple product {$\cdots$} from $A\;\times\;A\;\times\;A\;to\;A$ can be defined in a canonical way. If A is also the dual of some Banach space $A_{*}$, then A is said to be a JBW triple. A projection R on A is said to be structural if the identity {Ra, b, Rc} = R{a, Rb, c, }holds. On $JBW^{*}-triples$, structural projections being algebraic objects by definition have also some interesting metric properties, and it is possible to give a full characterization of structural projections in terms of the norm of the predual $A_{*}$ of A. It is shown, that the class of structural projections on A coincides with the class of the adjoints of neutral GL-projections on $A_{*}$. Furthermore, the class of GL-projections on $A_{*}$ is naturally ordered and is completely ortho-additive with respect to L-orthogonality.

• Journal of Information Technology Services
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• v.7 no.4
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• pp.221-230
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• 2008

Green's relations are five equivalence relations that characterize the elements of a semigroup in terms of the principal ideals. The J relation is one of Green's relations. Although there are known algorithms that can compute Green relations, they are not useful for finding all J relations in the semigroup of all $n{\times}n$ Boolean matrices. Its computation requires multiplication of three Boolean matrices for each of all possible triples of $n{\times}n$ Boolean matrices. The size of the semigroup of all $n{\times}n$ Boolean matrices grows exponentially as n increases. It is easy to see that it involves exponential time complexity. The computation of J relations over the $5{\times}5$ Boolean matrix is left an unsolved problem. The paper shows theorems that can reduce the computation time, discusses an algorithm for efficient J relation computation whose design reflects those theorems and gives its execution results.

• Communications of the Korean Mathematical Society
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• v.34 no.1
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• pp.105-111
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• 2019

Let $Y{\subset}{\mathbb{P}}^3$ be a degree d reduced curve with only planar singularities. We prove that $h^i({\mathcal{I}}_Y(t))=0$, i = 1, 2, for all $t{\geq}d-2$. We use this result and linkage to construct some triples (d, g, s), $d>s^2$, with very large g for which there is a smooth and connected curve of degree d and genus g, $h^0({\mathcal{I}}_C(s))=1$ and describe the Hartshorne-Rao module of C.

• Annual Conference on Human and Language Technology
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• 2023.10a
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• pp.726-729
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• 2023

본 논문에서는 대화 중 발화에서 페르소나 트리플을 추출하는 방법을 연구한다. 발화 문장과 그에 해당하는 트리플 쌍을 활용하여 발화 문장 혹은 페르소나 문장이 주어졌을 때 그로부터 페르소나 트리플을 추출하도록 모델을 멀티 태스크 러닝 방식으로 학습시킨다. 모델은 인코더-디코더 구조를 갖는 사전학습 언어모델 BART [1]와 T5 [2]를 활용하며 relation 추출과 tail 추출의 두 가지 태스크를 각각 인코더, 디코더 위에 head를 추가하여 학습한다. Relation 추출은 분류로, tail 추출은 생성 문제로 접근하도록 하여 최종적으로 head, relation, tail의 구조를 갖는 페르소나 트리플을 추출하도록 한다. 실험에서는 BART와 T5를 활용하여 각 태스크에 대해 다른 학습 가중치를 두어 훈련시켰고, 두 모델 모두 relation과 tail을 추출하는 태스크 정확도에 있어서 90% 이상의 높은 점수를 보임을 확인했다.

• Journal of KIISE
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• v.41 no.9
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• pp.674-685
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• 2014

The Knowledge service system needs to infer a new knowledge from indicated knowledge to provide its effective service. Most of the Knowledge service system is expressed in terms of ontology. The volume of knowledge information in a real world is getting massive, so effective technique for massive data of ontology is drawing attention. This paper is to provide the method to infer massive data-ontology to the extent of RDFS, based on cloud computing environment, and evaluate its capability. RDFS inference suggested in this paper is focused on both the method applying MapReduce based on RDFS meta table, and the method of single use of cloud computing memory without using MapReduce under distributed file computing environment. Therefore, this paper explains basically the inference system structure of each technique, the meta table set-up according to RDFS inference rule, and the algorithm of inference strategy. In order to evaluate suggested method in this paper, we perform experiment with LUBM set which is formal data to evaluate ontology inference and search speed. In case LUBM6000, the RDFS inference technique based on meta table had required 13.75 minutes(inferring 1,042 triples per second) to conduct total inference, whereas the method applying the cloud computing memory had needed 7.24 minutes(inferring 1,979 triples per second) showing its speed twice faster.

• Journal of the Korean Society for Library and Information Science
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• v.57 no.1
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• pp.93-114
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• 2023

Information extraction can facilitate the intensive analysis of documents by providing semantic triples which consist of named entities and their relations recognized in the texts. However, most of the research so far has been carried out separately for named entity recognition and relation extraction as individual studies, and as a result, the effective performance evaluation of the entire information extraction systems was not performed properly. This paper introduces two models of end-to-end information extraction that can extract various entity names in clinical records and their relationships in the form of semantic triples, namely pipeline and joint models and compares their performances in depth. The pipeline model consists of an entity recognition sub-system based on bidirectional GRU-CRFs and a relation extraction module using multiple encoding scheme, whereas the joint model was implemented with a single bidirectional GRU-CRFs equipped with multi-head labeling method. In the experiments using i2b2/VA 2010, the performance of the pipeline model was 5.5% (F-measure) higher. In addition, through a comparative experiment with existing state-of-the-art systems using large-scale neural language models and manually constructed features, the objective performance level of the end-to-end models implemented in this paper could be identified properly.