• KIPS Transactions on Software and Data Engineering
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• v.10 no.10
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• pp.399-406
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• 2021

With the steady growth of the content industry, the need for research that automatically recommending content suitable for individual tastes is increasing. In order to improve the accuracy of automatic content recommendation, it is needed to fuse existing recommendation techniques using users' preference history for contents along with recommendation techniques using content metadata or features extracted from the content itself. In this work, we propose a new graph-based music recommendation method which learns an LSTM-based classification model to automatically extract appropriate tagging words from sound data and apply the extracted tagging words together with the users' preferred music lists and music metadata to graph-based music recommendation. Experimental results show that the proposed method outperforms existing recommendation methods in terms of the recommendation accuracy.

• Journal of Korea Multimedia Society
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• v.13 no.8
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• pp.1183-1193
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• 2010

The pyramid graph is well known in parallel processing as a interconnection network topology based on regular square mesh and tree architectures. The enhanced pyramid graph is an alternative architecture by exchanging mesh into the corresponding torus on the base for upgrading performance than the pyramid. In this paper, we adopt a strategy of classification into two disjoint groups of edges in regular square torus as a basic sub-graph constituting of each layer in the enhanced pyramid graph. Edge set in the torus graph is considered as two disjoint sub-sets called NPC(represents candidate edge for neighbor-parent) and SPC(represents candidate edge for shared-parent) whether the parents vertices adjacent to two end vertices of the corresponding edge have a relation of neighbor or sharing in the upper layer of the enhanced pyramid graph. In addition, we also introduce a notion of shrink graph to focus only on the NPC-edges by hiding SPC-edges within the shrunk super-vertex on the resulting shrink graph. In this paper, we analyze that the lower and upper bounds on the number of NPC-edges in a Hamiltonian cycle constructed on $2^n{\times}2^n$ torus is $2^{2n-2}$ and $3{\cdot}2^{2n-2}$ respectively. By expanding this result into the enhanced pyramid graph, we also prove that the maximum number of NPC-edges containable in a Hamiltonian cycle is $4^{n-1}$-2n+1 in the n-dimensional enhanced pyramid.

• Journal of Korean Elementary Science Education
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• v.31 no.4
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• pp.490-500
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• 2012

This study was to examine elementary male and female students' spatial abilities, science process skills, and graph construction and interpretation abilities in order to understand the effect that their spatial abilities and science process skills would have on their graph abilities. To conduct this study, total 12 classes of 435 pupils, 6 classes each from grades 5 and 6 in elementary schools were selected for subjects. The number of male student was 207 and that of female one was 228 of them. And previous test papers of spatial abilities, of science process abilities, and of graph abilities were retouched and updated for reuse in new tests. The results of this study are briefed as follows: Firstly, when spatial abilities for male and female group were compared, female group showed a little higher rate of correct answering than male, but not providing statistically significant gap. Secondly, the science process skill tests revealed basic process skills of both groups were more excellent than their integrated process skills, while female group was found to have more correct answers than male, all of which were proving statistical distinction. Thirdly, of graphing skills for two groups, the graph interpretation skills turned out to be better than the graph construction skills, with female group scoring higher than male and with meaningful difference. Fourthly, both between spatial abilities and graph abilities, and between science process skills and graph abilities, static correlations existed with statistical meaning. In other words, those with higher spatial abilities or science process skills were to do better in constructing and interpreting graphs.

• Journal of the Korean Institute of Intelligent Systems
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• v.15 no.6
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• pp.759-764
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• 2005

In this paper we describe a face recognition using EBGM(Elastic Bunch Graph Matching) method. Usally, the PCA and LDA based face recognition method with the low-dimensional subspace representation use holistic image of faces, but this study uses local features such as a set of convolution coefficients for Gabor kernels of different orientations and frequencies at fiducial points including the eyes, nose and mouth. At pre-recognition step, all images are represented with same size face graphs and they are used to recognize a face comparing with each similarity for all images. The proposed algorithm has less computation time due to simplified face graph than conventional EBGM method and the fuzzy matching method for calculating the similarity of face graphs renders more face recognition results.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.4A
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• pp.350-359
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• 2010

In this paper, we provide a subchannel allocation algorithm for a femtocell system with OFDMA. This algorithm aims to maximize the minimum number of allocated subchannels among all femtocells and in addition, to maximize the total usage of subchannels in all femtocells. The subchannel allocation algorithm consists of three steps: constructing an interference graph, coloring algorithm, and mapping subchannels to colors. In the first step, the femtocell system is modelled by an interference graph, in which each femtocell is modeled as a node and two nodes that interfere with each other are connected by an edge. Based on this interference graph, by using a coloring scheme and mapping subchannels to each color, we can allocate subchannels to each femtocell. Finally, the performance of this algorithm is provided by simulation.

• Journal of the Korea Society of Computer and Information
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• v.16 no.8
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• pp.85-93
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• 2011

In this paper, we analyzed the function elements of the Integrated meter reading system based on PLC which is working in Mok-dong, Seoul and studied how to improve the vulnerability. Also we propose an efficient method for the estimation of abnormal life status through frequency domain processing of utility meter readings. We found out that even after removing the high-frequency components from the raw meter data, the shape of the graph still maintains the original graph characteristics. The graph of the inverse transformed data has simpler and smoother curve than the original graph pattern. The original graph is not good to be used in deciding whether the residence's life pattern is normal or not. We could find out that the graph which is processed frequency signal has simple and intuitive graph pattern.

• The Journal of the Acoustical Society of Korea
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• v.15 no.1
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• pp.54-60
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• 1996

In most pattern recognition and image understanding applications, images are degraded by noise and other distortions. Therefore, it is more relevant to decide how similar two objects are rather than to decide whether the two are exactly the same. In this paper, we propose a method for recognizing degraded symbols using a distance measure between two graphs representing the symbols. a symbol is represented as a graph consisting of nodes and edges based on the run graph concept. The graph is then transformed into a reference model graph with production rule containing the embedding transform. The symbols are recognized by using the distance measure which is estimated by using the number of production rules used and the structural homomorphism between a transformed graph and a model graph. the proposed approach is applies to the recognition of non-note musical symbols and the result are given.

• Journal of KIISE:Computer Systems and Theory
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• v.33 no.5
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• pp.267-281
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• 2006

PPI(Protein-Protein Interaction) data has information about the organism has maintained a life with some kind of mechanism. So, it is used in study about cure research back, cause of disease, and new medicine development. This PPI data has been increased by geometric progression because high throughput methods are developed such as Yeast-two-hybrid, Mass spectrometry, and Correlated mRNA expression. So, it is impossible that a person directly manage and analyze PPI data. Fortunately, PPI data is able to abstract the graph which has proteins as nodes, interactions as edges. Consequently, Graph theory plentifully researched from the computer science until now is able to be applied to PPI data successfully. In this paper, we introduce Proteinca(PROTEin INteraction CAbaret) workbench system for easily managing, analyzing and visualizing PPI data. Proteinca assists the user understand PPI data intuitively as visualizing a PPI data in graph and provide various analytical function on graph theory. And Protenica provides a simplified visualization with gravity-rule.

• Journal of Korea Multimedia Society
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• v.25 no.3
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• pp.493-501
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• 2022

This paper is a study on context-sensitive spelling error correction and uses the Korean WordNet (KorLex)[1] that defines the relationship between words as a graph to improve the performance of the correction[2] based on the vector information of the word embedded in the correction technique. The Korean WordNet replaced WordNet[3] developed at Princeton University in the United States and was additionally constructed for Korean. In order to learn a semantic network in graph form or to use it for learned vector information, it is necessary to transform it into a vector form by embedding learning. For transformation, we list the nodes (limited number) in a line format like a sentence in a graph in the form of a network before the training input. One of the learning techniques that use this strategy is Deepwalk[4]. DeepWalk is used to learn graphs between words in the Korean WordNet. The graph embedding information is used in concatenation with the word vector information of the learned language model for correction, and the final correction word is determined by the cosine distance value between the vectors. In this paper, In order to test whether the information of graph embedding affects the improvement of the performance of context- sensitive spelling error correction, a confused word pair was constructed and tested from the perspective of Word Sense Disambiguation(WSD). In the experimental results, the average correction performance of all confused word pairs was improved by 2.24% compared to the baseline correction performance.

• Journal of the Korea Society of Computer and Information
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• v.28 no.9
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• pp.167-176
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• 2023

In this paper, we designed and implemented a graph assessment module that can evaluate graphs in an programming assessment system based on text and numbers. The assessment method of the graph assessment module is self-evaluation that outputs two graphs generated by codes submitted by learners and by answers, automatic-evaluation that converts each graph image into an array, and gives feedback if it is wrong. The data used to generate the graph can be inputted directly or used from external data, and the method of generatng graph that can be evaluated is MATLAB style in matplotlib, and the graph shape that can be evaluated is presented in mathematics and curriculum. Through expert review, it was confirmed that the content elements of the assessment module, the possibility of learning, and the validity of the learner's needs were met. The graph assessment module developed in this study has expanded the evaluation area of the programming automatic asssessment system and is expected to help students learn data visualization.