• Journal of KIISE:Databases
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• v.29 no.4
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• pp.274-284
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• 2002

Queries on XML are based on paths in the data graph, which is represented as an edge labeled graph model. All proposed query languages for XML express queries using regular expressions to traverse arbitrary paths in the data graph. A meaningful query usually has several regular path expressions in it, but much of recent research is more concerned with optimizing a single path expression. In this paper, we present an efficient technique to process multiple path expressions in a query. We developed a data structure named as the path identifier(PID) to identify whether two given nodes lie on the fame path in the data graph or not, and utilized the PID for efficient processing of multiple path expressions. We implement our technique and present preliminary performance results.

• Architectural research
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• v.17 no.2
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• pp.57-64
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• 2015

In architectural planning, previous cases of similar spatial program provide important data for architectural design. Case-based reasoning (CBR) paradigm in the field of architectural design is closely related to the designing behavior of a planner who makes use of similar architectural designs and spatial programs in the past. In CBR, spatial graph can be constituted with most fundamental data, which can provide a method of searching spatial program by using visual graphs. This study developed a system for CBR that can analyze the similarity through graph comparison and search for buildings. This is an integrated system that is able to compare space similarity of different buildings and analyze their types, in addition to the analysis on a space within a single structure.

• The Bulletin of The Korean Astronomical Society
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• v.44 no.1
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• pp.79.1-79.1
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• 2019

We present an algorithm for the fast computation of the general N-point spatial correlation functions of any discrete point set embedded within an Euclidean space of ${\mathbb{R}}n$. Utilizing the concepts of kd-trees and graph databases, we describe how to count all possible N-tuples in binned configurations within a given length scale, e.g. all pairs of points or all triplets of points with side lengths < rmax. Through benchmarking we show the computational advantage of our new graph-based algorithm over more traditional methods. We show that all 3-point configurations up to and beyond the Baryon Acoustic Oscillation scale (~200 Mpc in physical units) can be performed on current Sloan Digital Sky Survey (SDSS) data in reasonable time. Finally we present the first measurements of the 4-point correlation function of ~0.5 million SDSS galaxies over the redshift range 0.43< z <0.7. We present the publicly available code GRAMSCI (GRAph Made Statistics for Cosmological Information; bitbucket.org/csabiu/gramsci), under a GNU General Public License.

• Journal of the Korean Association of Geographic Information Studies
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• v.25 no.4
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• pp.163-180
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• 2022

Real estate data can be big data. Because the amount of real estate data is growing rapidly and real estate data interacts with various fields such as the economy, law, and crowd psychology, yet is structured with complex data layers. The existing Relational Database tends to show difficulty in handling various relationships for managing real estate big data, because it has a fixed schema and is only vertically extendable. In order to improve such limitations, this study constructs the real estate data in a Graph Database and verifies its usefulness. For the research method, we modeled various real estate data on MySQL, one of the most widely used Relational Databases, and Neo4j, one of the most widely used Graph Databases. Then, we collected real estate questions used in real life and selected 9 different questions to compare the query times on each Database. As a result, Neo4j showed constant performance even in queries with multiple JOIN statements with inferences to various relationships, whereas MySQL showed a rapid increase in its performance. According to this result, we have found out that a Graph Database such as Neo4j is more efficient for real estate big data with various relationships. We expect to use the real estate Graph Database in predicting real estate price factors and inquiring AI speakers for real estate.

• Journal of the Korea Society of Computer and Information
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• v.18 no.7
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• pp.111-123
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• 2013

To verify software vulnerability, the method of conjecturing software structure and then testing the software based on the conjectured structure has been highlighted. To utilize the method, an efficient way to conjecture software structure is required. The popular graph and tree methods such as DFG(Data Flow Graph), CFG(Control Flow Graph) and CFA(Control Flow Automata) have a serious drawback. That is, they cannot express software in a hierarchical fashion. In this paper, we propose a method to overcome the drawback. The proposed method applies various input data to a binary code, generate CFG's based on the code output and construct a HCFG (Hierarchical Control Flow Graph) to express the generated CFG's in a hierarchical structure. The components required for HCFG and progressive algorithm to construct HCFG are also proposed. The proposed method is verified through constructing the software architecture of an open SMTP(Simple Mail Transfer Protocol) server program. The structure generated by the proposed method and the real program structure are compared and analyzed.

• Journal of the Korean Data and Information Science Society
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• v.23 no.5
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• pp.971-981
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• 2012

Google map has become one of the most recognized and comfortable means for providing statistical information of geographically referenced data. In this article, we introduce R functions to embed google map images on R interface and develop a function to represent statistical graphs such as bar graph, pie chart, and rectangle graph on a google map images.

• Journal of the Korean Institute of Telematics and Electronics A
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• v.33A no.2
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• pp.196-204
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• 1996

This paper presents a new scheduling algorithm, which is the most improtant subtask in the high level synthesis. The proposed algorithm performs scheduling in consideration of resource sharing concept based on characteristics of conditionsla bransches in the intermediate data structure. CDFG (control data flow graph) generated by a VHDL analyzer. This algorithm constructs a conditon graph based on time frame of each operation using both the ASAP and the ALAP scheduling algorithm. The conditon priority is obtained from the condition graph constructed from each conditional brance. The determined condition priority implies the sequential order of transforming the CDFG with conditonal branches into the CDFG without conditional branches. To minimize resource cost, the CDFG with conditional branches are transformed into the CDFG without conditonal brancehs according to the condition priority. Considering the data dependency, the hardware constraints, and the data execution time constraints, each operation in the transformed CDFG is assigned ot control steps. Such assigning of unscheduled operations into contorl steps implies the performance of the scheduling in the consecutive movement of operations. The effectiveness of this algorithm is hsown by the experiment for the benchmark circuits.

• ETRI Journal
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• v.38 no.3
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• pp.540-550
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• 2016

Spectral clustering is a powerful tool for exploratory data analysis. Many existing spectral clustering algorithms typically measure the similarity by using a Gaussian kernel function or an undirected k-nearest neighbor (kNN) graph, which cannot reveal the real clusters when the data are not well separated. In this paper, to improve the spectral clustering, we consider a robust similarity measure based on the shared nearest neighbors in a directed kNN graph. We propose two novel algorithms for spectral clustering: one based on the number of shared nearest neighbors, and one based on their closeness. The proposed algorithms are able to explore the underlying similarity relationships between data points, and are robust to datasets that are not well separated. Moreover, the proposed algorithms have only one parameter, k. We evaluated the proposed algorithms using synthetic and real-world datasets. The experimental results demonstrate that the proposed algorithms not only achieve a good level of performance, they also outperform the traditional spectral clustering algorithms.

• Journal of Korean Elementary Science Education
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• v.31 no.3
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• pp.321-333
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• 2012

The purpose of this study was to examine elementary school students' characteristics and difficulties in drawing and interpreting a line graph, and to present educational implications. Twenty five students(4th grader: 6, 5th grader: 9, and 6th grader: 10) at an elementary school participated in this study. We used a student's task which was about graphing on a given data table and interpreting his/her graph. The data table was on heating 200mL and 500mL of water and measuring their temperature at regular time intervals. We collected multiple source of data, and data analyzed based on the sub-variables of TOGS. The some results of this study are as follows: First, five children (20.0%), especially two of 10 sixth graders (20.0%), could not construct a line graph about a given data table. Second, twenty students (80.0%) had the ability on 'Scaling axes' and on 'Assigning variables to the axes', however, only a student understood why the time is on the longitudinal axis and the temperature is on the vertical axis. Third, in the case of 'Plotting points', twelve children (48.0%) could drew two graphs on a coordinate. Fourth, in the case of 'Selecting the corresponding value for Y (or X)', twenty student had little difficulty. on 'Describing the relationship between variables', seventeen students (68.0%) understood the relationship between time and temperature of water, and the relationship between temperature and amount of water. Finally, eleven students (44%) had the ability on 'Interrelating and extrapolation graphs.' Educational implications are also presented in this paper.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.7
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• pp.1327-1334
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• 2017

The Bubble sort graph is node symmetric, and can be used in the data sorting algorithm. In this research we propose and analyze that Half Bubble sort graph that improved the network cost of Bubble sort graph. The Half Bubble sort graph's number of node is n!, and its degree is ${\lfloor}n/2{\rfloor}+1$. The Half Bubble sort graph's degree is $${\sim_=}0.5$$ times of the Bubble sort, and diameter is $${\sim_=}0.9$$ times of the Bubble sort. The network cost of the Bubble sort graph is $${\sim_=}0.5n^3$$, and the network cost of the half Bubble sort graph is $${\sim_=}0.2n^3$$. We have proved that half bubble sort graph is a sub graph of the bubble sort graph. In addition, we proposed a routing algorithm and analyzed the diameter. Finally, network cost is compared with the bubble sort graph.