• Title/Summary/Keyword: graph mining

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AUTOMORPHISMS OF THE ZERO-DIVISOR GRAPH OVER 2 × 2 MATRICES

  • Ma, Xiaobin;Wang, Dengyin;Zhou, Jinming
    • Journal of the Korean Mathematical Society
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    • v.53 no.3
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    • pp.519-532
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    • 2016
  • The zero-divisor graph of a noncommutative ring R, denoted by ${\Gamma}(R)$, is a graph whose vertices are nonzero zero-divisors of R, and there is a directed edge from a vertex x to a distinct vertex y if and only if xy = 0. Let $R=M_2(F_q)$ be the $2{\times}2$ matrix ring over a finite field $F_q$. In this article, we investigate the automorphism group of ${\Gamma}(R)$.

Underground Mine Design and Stability Analysis at a Limestone Mine (석회석광산의 갱내채광설계 및 안정성평가)

  • Koo, Chung-Mo;Jeon, Seok-Won;Lee, In-Woo
    • Tunnel and Underground Space
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    • v.18 no.4
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    • pp.243-251
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    • 2008
  • Recently, the mining methods are changing from surface mining to underground mining because of the increment of the environmental issues and legal regulations. Therefore, the stability of underground openings is a major concern for the safety and productivity of mining operations. In this paper, a survey of structural geology and discontinuities were carried out at a limestone mine. The relevant mechanical properties of rocks were determined by the laboratory tests and rock mass classifications (RMR and Q-system) for the mine design and input data for the stability analysis. The dimensions of unsupported span for underground openings and pillar were decided based on the RMR values of rock mass classifications. The stability analysis for the suggested mine design was examined through the empirical methods (stability graph method and critical span curve) and 3-D numerical analysis (Visual-FEA).

Text-mining Based Graph Model for Keyword Extraction from Patent Documents (특허 문서로부터 키워드 추출을 위한 위한 텍스트 마이닝 기반 그래프 모델)

  • Lee, Soon Geun;Leem, Young Moon;Um, Wan Sup
    • Journal of the Korea Safety Management & Science
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    • v.17 no.4
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    • pp.335-342
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    • 2015
  • The increasing interests on patents have led many individuals and companies to apply for many patents in various areas. Applied patents are stored in the forms of electronic documents. The search and categorization for these documents are issues of major fields in data mining. Especially, the keyword extraction by which we retrieve the representative keywords is important. Most of techniques for it is based on vector space model. But this model is simply based on frequency of terms in documents, gives them weights based on their frequency and selects the keywords according to the order of weights. However, this model has the limit that it cannot reflect the relations between keywords. This paper proposes the advanced way to extract the more representative keywords by overcoming this limit. In this way, the proposed model firstly prepares the candidate set using the vector model, then makes the graph which represents the relation in the pair of candidate keywords in the set and selects the keywords based on this relationship graph.

Post-pillars design for safe exploitation at Trepça hard rock mine (Kosovo) based on numerical modeling

  • Ibishi, Gzim;Genis, Melih;Yavuz, Mahmut
    • Geomechanics and Engineering
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    • v.28 no.5
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    • pp.463-475
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    • 2022
  • In the mine exploitation stage; one of the critical issues is the stability assessment of post-pillars. The instability of post-pillars leads to serious safety hazards in mining operations. The focus of this study is to assess the stability of post-pillars in the 130# stope in the central ore body at Trepça hard rock mine by employing both conventional (i.e., critical span curve) and numerical methods (i.e., FLAC3D). Moreover, a new numerical based index (i.e., Pillar Yield Ratio-PYR) was proposed. The aim of PYR index is to determine a border line between stable, potentially unstable, and failure state of post-pillars at a specific mine site. The critical value of pillar width to height ratio is 2.5 for deep production stopes (e.g., > 800 m). Results showed that pillar size, mining height and mining depth significantly have affected the post-pillar stability. The reliability of numerical based index (i.e., PYR) is verified based on empirical underground pillar stability graph developed by Lunder, 1994. The proposed pillar yield ratio index and pillar stability graph can be used as a design tool in new mining areas at Trepça hard rock mine and for other situations with similar geotechnical conditions.

An efficient approach of avoiding extensions of duplicated graph patterns in cyclic graph mining (순환 그래프 마이닝에서 중복된 그래프 패턴의 확장을 피하는 효율적인 기법)

  • No, Young-Sang;Yun, Un-Il;Pyun, Gwang-Bum;Ryang, Heung-Mo;Lee, Gang-In;Ryu, Keun-Ho;Lee, Kyung-Min
    • Journal of the Korea Society of Computer and Information
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    • v.16 no.12
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    • pp.33-41
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    • 2011
  • From Complicated graph structures, duplicated operations can be executed and the operations give low efficiency. In this paper, we propose an efficient graph mining algorithm of minimizing the extension of duplicated graph patterns in which the priorities of cyclic edges are considered. In our approach, the cyclic edges with lower priorities are first extended and so duplicated extensions can be reduced. For performance test, we implement our algorithm and compare our algorithm with a state of the art, Gaston algorithm. Finally, We show that ours outperforms Gaston algorithm.

BINGO: Biological Interpretation Through Statistically and Graph-theoretically Navigating Gene $Ontology^{TM}$

  • Lee, Sung-Geun;Yang, Jae-Seong;Chung, Il-Kyung;Kim, Yang-Seok
    • Molecular & Cellular Toxicology
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    • v.1 no.4
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    • pp.281-283
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    • 2005
  • Extraction of biologically meaningful data and their validation are very important for toxicogenomics study because it deals with huge amount of heterogeneous data. BINGO is an annotation mining tool for biological interpretation of gene groups. Several statistical modeling approaches using Gene Ontology (GO) have been employed in many programs for that purpose. The statistical methodologies are useful in investigating the most significant GO attributes in a gene group, but the coherence of the resultant GO attributes over the entire group is rarely assessed. BINGO complements the statistical methods with graph-theoretic measures using the GO directed acyclic graph (DAG) structure. In addition, BINGO visualizes the consistency of a gene group more intuitively with a group-based GO subgraph. The input group can be any interesting list of genes or gene products regardless of its generation process if the group is built under a functional congruency hypothesis such as gene clusters from DNA microarray analysis.

An Improved Rectangular Decomposition Algorithm for Data Mining (데이터 마이닝을 위한 개선된 직사각형 분해 알고리즘)

  • Song, Ji-Young;Im, Young-Hee;Park, Dai-Hee
    • The KIPS Transactions:PartB
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    • v.10B no.3
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    • pp.265-272
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    • 2003
  • In this paper, we propose a novel improved algorithm for the rectangular decomposition technique for the purpose of performing data mining from large scaled database in a dynamic environment. The proposed algorithm performs the rectangular decompositions by transforming a binary matrix to bipartite graph and finding bicliques from the transformed bipartite graph. To demonstrate its effectiveness, we compare the proposed one which is based on the newly derived mathematical properties with those of other methods with respect to the classification rate, the number of rules, and complexity analysis.

Frequent Patterns Mining using only one-time Database Scan (한 번의 데이터베이스 탐색에 의한 빈발항목집합 탐색)

  • Chai, Duck-Jin;Jin, Long;Lee, Yong-Mi;Hwang, Bu-Hyun;Ryu, Keun-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.1
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    • pp.15-22
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    • 2008
  • In this paper, we propose an efficient algorithm using only one-time database scan. The proposed algorithm creates the bipartite graph which indicates relationship of large items and transactions including the large items. And then we can find large itemsets using the bipartite graph. The bipartite graph is generated when database is scanned to find large items. We can't easily find transactions which include large items in the large database. In the bipartite graph, large items and transactions are linked each other. So, we can trace the transactions which include large items through the link information. Therefore the bipartite graph is a indexed database which indicates inclusion relationship of large items and transactions. We can fast find large itemsets because proposed method conducts only one-time database scan and scans indexed the bipartite graph. Also, it don't generate candidate itemsets.

An Efficient Large Graph Clustering Technique based on Min-Hash (Min-Hash를 이용한 효율적인 대용량 그래프 클러스터링 기법)

  • Lee, Seok-Joo;Min, Jun-Ki
    • Journal of KIISE
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    • v.43 no.3
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    • pp.380-388
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    • 2016
  • Graph clustering is widely used to analyze a graph and identify the properties of a graph by generating clusters consisting of similar vertices. Recently, large graph data is generated in diverse applications such as Social Network Services (SNS), the World Wide Web (WWW), and telephone networks. Therefore, the importance of graph clustering algorithms that process large graph data efficiently becomes increased. In this paper, we propose an effective clustering algorithm which generates clusters for large graph data efficiently. Our proposed algorithm effectively estimates similarities between clusters in graph data using Min-Hash and constructs clusters according to the computed similarities. In our experiment with real-world data sets, we demonstrate the efficiency of our proposed algorithm by comparing with existing algorithms.

Workflow Specification Mining on Workflow Logs (워크플로우 로그에서 워크플로우 명세 탐사)

  • 정희택
    • Journal of the Korea Institute of Information and Communication Engineering
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    • v.6 no.8
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    • pp.1325-1335
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    • 2002
  • Workflow systems, automated business processing, have been generalized. In this paper, we propose a method to mine workflow specification on workflow logs. The method detects workflow specification considering cycle, AND and OR control flow between tasks. Also, we provide dynamic mining method to detect workflow specification in which log is generated.