• Journal of Information Technology Applications and Management
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• v.26 no.1
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• pp.65-75
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• 2019

As the use of semantic web based on XML increases in the field of data management, a lot of studies to extract useful information from the data stored in ontology have been tried based on association rule mining. Ontology data is advantageous in that data can be freely expressed because it has a flexible and scalable structure unlike a conventional database having a predefined structure. On the contrary, it is difficult to find frequent patterns in a uniformized analysis method. The goal of this study is to provide a basis for extracting useful knowledge from ontology by searching for frequently occurring subgraph patterns by applying transaction-based graph mining techniques to ontology schema graph data and instance graph data constituting ontology. In order to overcome the structural limitations of the existing ontology mining, the frequent pattern search methodology in this study uses the methodology used in graph mining to apply the frequent pattern in the graph data structure to the ontology by applying iterative node chunking method. Our suggested methodology will play an important role in knowledge extraction.

• Proceedings of the IEEK Conference
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• 2000.07b
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• pp.803-806
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• 2000

The correspondence problem is known to be difficult to solve because false positives and false negatives almost always exist in real image sequences. In this paper, we propose a robust feature tracking algorithm considering incomplete trajectories such as entering and/or vanishing trajectories. We solve the correspondence problem as the optimal graph search problem, by considering false feature points and by properly reflecting motion characteristics. The proposed algorithm finds a local optimal correspondence so that the effect of false feature points can be minimized in the decision process. The time complexity of the proposed graph search algorithm is given by O(mn) in the best case and O(m$^2$n) in the worst case, where m and n are the number of feature points in two consecutive frames. The proposed algorithm can find trajectories correctly and robustly, which has been shown by experimental results.

• KIISE Transactions on Computing Practices
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• v.23 no.8
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• pp.492-497
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• 2017

A hypergraph consists of a set of nodes and hyperedges that connect an arbitrary number of nodes. We employ graph traversal algorithms such as BFS and DFS to analyze or explore hypergraph data. However, the conventional BFS and DFS do not consider the structural characteristics of hyperedges. In this paper, we propose a method to record visited edges and nodes during the traversal algorithm for data stored in hypergraphDB. In the experiments, we conduct various hypergraph analyses that utilize traversal algorithms and show that our method achieves a fewer number of database accesses and faster processing time than the conventional one.

• Journal of Korea Society of Industrial Information Systems
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• v.10 no.2
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• pp.26-31
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• 2005

In this paper, we present the document summarizers which are simpler and more condense than the existing ones generally used in the web search engines. This method is a statistic-based summarization method using the concept of the complete graph. We suppose that each sentence as a vertex and the similarity between two sentences as a link of the graph. We compare this summarizer with those of Clustering and MMR techniques which are well-known as the good summarization methods. For the comparison, we use FScore using the summarization results generated by human subjects. Our experimental results verify the accuracy of this method, being about $30\%$ better than the others.

• Journal of the Korean Institute of Intelligent Systems
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• v.16 no.6
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• pp.677-682
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• 2006

Multi-domain design is difficult because such systems tend to be complex and include a mixtures of electrical, mechanical, hydraulic, and thermal components. To design an optimal system, unified and automated procedure with efficient search technique is required. This paper introduces design method for multi-domain system to obtain design solutions automatically, combining bond graph which is domain independent modeling tool and genetic programming which is well recognized as a powerful tool for open-ended search. The suggested design methodology has been applied for design of electric fitter, electric printer drive, and and pump system as a proof of concept for this approach.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.7 no.5
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• pp.993-1001
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• 2003

A RDB Storage Model based on the Edge-Labeled Graph is suggested for store the XML instance in Relational Databases(RDB). The XML instance being stored is represented by Data Graph based on the Edge-Labeled Graph. Data Path Table, Element, Attribute, and Table Index Table values are extracted. Then Database Schema is defined, and the extracted values are stored using the Mapper. In order to support querry, Repository Model offers the translator translating XQL which is used as query language under XPATH, into SQL. In addition, it creates DBtoXML generator restoring the stored XML instance. As a result, storage relationship between the XML instance and proposed model structure can be expressed in terms of Graph-based Path, and it shows the possibility of easy search of random Element and Attribute information.

• Journal of Convergence for Information Technology
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• v.10 no.1
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• pp.139-148
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• 2020

As the internet and computer technology are developed, there is a need for service of traditional culture that can effectively search and create culture, history, and tradition-related materials in online contents. In this paper, we developed an RDF-based ontology retrieval service platform and verified usability and validity. This platform is divided into triple search, keyword search, network graph search, story search and management, curation management module. Based on this, the search results can be visualized based on the relationship between data, network graph search and story search can be used to easily understand the relationship between the keywords. An platform evaluation was conducted for verification, and it was evaluated that an intelligent search that can easily identify the relationship between information and shorten the analysis and search time than the existing search function.

• Journal of the Korean Society of Surveying, Geodesy, Photogrammetry and Cartography
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• v.31 no.5
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• pp.411-419
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• 2013

Research on developing algorithms for building modeling such as extracting outlines of the buildings and segmenting patches of the roofs using aerial images or LiDAR data are active. However, utilizing information from the building model is not well implemented yet. This study aims to propose a scheme for search identical or similar shape of buildings by utilizing graph topology pattern matching under the assumptions: (1) Buildings were modeled beforehand using imagery or LiDAR data, or (2) 3D building data from digital maps are available. Side walls, segmented roofs and footprints were represented as nodes, and relationships among the nodes were defined using graph topology. Topology graph database was generated and pattern matching was performed with buildings of various shapes. The results show that efficiency of the proposed method in terms of reliability of matching and database structure. In addition, flexibility in the search was achieved by altering conditions for the pattern matching. Furthermore, topology graph representation could be used as scale and rotation invariant shape descriptor.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.147-150
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• 2008

The real road network is regarded as a grid, and the grid is divided by fixed-sized cells. The path-finding is composed of two step searching. First searching travels on the abstract graph which is composed of a set of psuedo vertexes and a set of psuedo edges that are created by real road network and fixed-sized cells. The result of the first searching is a psuedo path which is composed of a set of selected psuedo edges. The cells intersected with the psuedo path are called as valid cells. The second searching travels with $A^*$ algorithm on valid cells. As pruning search space by removing the invalid cells, it would be possible to reduce the cost of exploring on real road network. In this paper, we present the method of creating the abstract graph and propose a path-finding algorithm on the abstract graph for extracting search space before traveling on real road network.

• Journal of KIISE:Computing Practices and Letters
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• v.16 no.6
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• pp.727-731
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• 2010

Recently, mobile life-log data are collected by mobile devices and used to recode one's life. In order to help a user search data, a mobile life-log semantic network is introduced for storing logs and retrieving associative information. However, associative search systems on common semantic networks in previous studies provide for a user with only found data as text to users. This paper proposes an associative search system for mobile life-log semantic network that supports selection and keyword associative search of which a process and result are a visualized graph representing associative data and their relationships when a user inputs a keyword for search. In addition, by using semantic abstraction, the system improves user's understanding of search result and simplifies the resulting graph. The system's usability was tested by an experiment comparing the system and a text-based search system.