• The KIPS Transactions:PartD
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• v.16D no.1
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• pp.27-42
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• 2009

In realizing ubiquitous computing, techniques of efficiently using the limited resource at client such as mobile devices are required. With a mobile device with limited amount of memory, the techniques of XML stream query processing should be employed to process queries over a large volume of XML data. Recently, several techniques were proposed which fragment XML documents into XML fragments and stream them for query processing at client. During query processing, there could be great difference in resource usage (query processing time and memory usage) depending on how the source XML documents are fragmented. As such, an efficient fragmentation technique is needed. In this paper, we propose an XML fragmentation technique whereby resource efficiency in query processing at client could be enhanced. For this, we first present a cost model of query processing over XML fragment stream. Then, we propose an algorithm for resource-efficient XML fragmentation. Through implementation and experiments, we showed that our fragmentation technique outperformed previous techniques both in processing time and memory usage. The contribution of this paper is to have made the techniques of query processing over XML fragment stream more feasible for practical use.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.475-486
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• 2009

Data cube plays an important role in multi-dimensional, multi-level data analysis. Meeting on-line analysis requirements of data stream, several cube structures have been proposed for OLAP on data stream, such as stream cube, flowcube, S-cube. Since it is costly to construct data cube and execute ad-hoc OLAP queries, more research works should be done considering efficient data structure, query method and algorithms. Stream cube uses H-cubing to compute selected cuboids and store the computed cells in an H-tree, which form the cuboids along popular-path. However, the H-tree layoutis disorderly and H-cubing method relies too much on popular path.In this paper, first, we propose $H^*$-tree, an improved data structure, which makes the retrieval operation in tree structure more efficient. Second, we propose an improved cubing method, $H^*$-cubing, with respect to computing the cuboids that cannot be retrieved along popular-path when an ad-hoc OLAP query is executed. $H^*$-tree construction and $H^*$-cubing algorithms are given. Performance study turns out that during the construction step, $H^*$-tree outperforms H-tree with a more desirable trade-off between time and memory usage, and $H^*$-cubing is better adapted to ad-hoc OLAP querieswith respect to the factors such as time and memory space.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.161-172
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• 2013

Metadata registry (MDR) is the international standard, developed by ISO/IEC for exchange and sharing data between databases. Many MDR systems are used in diverse domains such as medical service, bibliography, environment for sharing and integrating data. However, those systems have different physical structures individually because the MDR standard defines only the metamodel for registering and storing metadata. It causes heterogeneity between the system structures and requires additional cost to maintain interoperability. ISO/IEC 13249-8 Metadata Registry Access (MRA) is developing as an international standard to provide a consistent access facility to data stored in different metadata registries. However, MRA does not consider the relationships between the concepts (classes) defined in the MDR specification. It causes that incorrect query results returned from MDR systems. It also requires additional cost of modeling and rewriting queries to reflect each physical model. Therefore, this paper suggests eMRA which considers the relationships between the concepts in MDR. The comparative evaluations are described to show the advantages of eMRA. eMRA has superior performance in query modeling and referential integrity than MRA defined by the relationship between the concept of MDR.

• The KIPS Transactions:PartD
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• v.10D no.2
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• pp.233-246
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• 2003

The mediator-based system integrates heterogeneous information systems with the flexible manner. But it does not give much attention on the query optimization issues, especially for the query reusing. The other thing is that it does not use standardized metadata for schema matching. To improve this two issues, we propose mediator-based Distributed Information Integration System (DIIS) which uses query caching regarding performance and uses ISO/IEC 11179 metadata registry in terms of standardization. The DIIS is designed to provide decision-making support, which logically integrates the distributed heterogeneous business information systems based on the Web environment. We designed the system in the aspect of three-layer expression formula architecture using the layered pattern to improve the system reusability and to facilitate the system maintenance. The functionality and flow of core components of three-layer architecture are expressed in terms of process line diagrams and assembly line diagrams of Eriksson Penker Extension Model (EPEM), a methodology of an extension of UML. For the implementation, Supply Chain Management (SCM) domain is used. And we used the Web-based environment for user interface. The DIIS supports functions of query caching and query reusability through Query Function Manager (QFM) and Query Function Repository (QFR) such that it enhances the query processing speed and query reusability by caching the frequently used queries and optimizing the query cost. The DIIS solves the diverse heterogeneity problems by mapping MetaData Registry (MDR) based on ISO/IEC 11179 and Schema Repository (SCR).

• The Journal of the Korea Contents Association
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• v.19 no.1
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• pp.141-151
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• 2019

A network of graph data structure is used in many applications to represent interactions between entities. Recently, as the size of the network to be processed due to the development of the big data technology is getting larger, it becomes more difficult to handle it in one server, and thus the necessity of distributed processing is also increasing. In this paper, we propose a distributed processing system for efficiently performing subgraph and stores. To reduce unnecessary searches, we use statistical information of the data to determine the search order through probabilistic scoring. Since the relationship between the vertex and the degree of the graph network may show different characteristics depending on the type of data, the search order is determined by calculating a score to reduce unnecessary search through a different scoring method for a graph having various distribution characteristics. The graph is sequentially searched in the distributed servers according to the determined order. In order to demonstrate the superiority of the proposed method, performance comparison with the existing method was performed. As a result, the search time is improved by about 3 ~ 10% compared with the existing method.

• Journal of Korean Society of Archives and Records Management
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• v.21 no.3
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• pp.61-78
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• 2021

Records on Japanese "Comfort Women" have been individually managed by private sectors or institutions, and some are provided as digital archives on the Internet. However, records of digital archives differ in the composition and representation of metadata by individual institutions. Meanwhile, there is a lack of a consistent structure to describe the relationships between and among these records, leading to their fragmentation and disconnectedness. This paper proposes a knowledge model for interlinking the digital archival resources and builds a knowledge graph by integrating the records from distributed digital archives. It derives common elements by analyzing metadata from the diverse digital archives and expresses them in standard vocabularies to semantically describe multiple entities and relationships of the digital archival resources. In particular, the study includes the refinement of collected data to search and thread dispersed records and the enrichment of external data to provide significant contextual information of records. An evaluation of the knowledge graph is performed via a query measuring the (dis)connectivity between the distributed records. As a result, the knowledge graph is capable of interlinking and retrieving fragmented records, providing substantial contextual information on the records with external data enrichment, and searching accurately to match the user's intentions through semantic-based queries.

• Journal of Convergence for Information Technology
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• v.10 no.12
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• pp.15-21
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• 2020

Although IoT systems are used in a variety of heterogeneous environments as cloud environments develop, all IoT devices are not provided with reliable protocols and services. This paper proposes an IoT data management technique that can extend the IoT cloud environment to an n-layer multi-level structure so that information collected from different heterogeneous IoT devices can be efficiently sorted and processed. The proposed technique aims to classify and process IoT information by transmitting routing information and weight information through wireless data link data collected from heterogeneous IoT devices. The proposed technique not only delivers information classified from IoT devices to the corresponding routing path but also improves the efficiency of IoT data processing by assigning priority according to weight information. The IoT devices used in the proposed technique use each other's reliable protocols, and queries for other IoT devices locally through a local cloud composed of hierarchical structures have features that ensure scalability because they maintain a certain cost.y channels of IoT information in order to make the most of the multiple antenna technology.

• 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.27 no.12
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• pp.59-68
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• 2022

This paper presents a method for 1:1 verification by comparing the similarity between the given real product image and the drawing image. The proposed method combines two existing CNN-based deep learning models to construct a Siamese Network. After extracting the feature vector of the image through the FC (Fully Connected) Layer of each network and comparing the similarity, if the real product image and the drawing image (front view, left and right side view, top view, etc) are the same product, the similarity is set to 1 for learning and, if it is a different product, the similarity is set to 0. The test (inference) model is a deep learning model that queries the real product image and the drawing image in pairs to determine whether the pair is the same product or not. In the proposed model, through a comparison of the similarity between the real product image and the drawing image, if the similarity is greater than or equal to a threshold value (Threshold: 0.5), it is determined that the product is the same, and if it is less than or equal to, it is determined that the product is a different product. The proposed model showed an accuracy of about 71.8% for a query to a product (positive: positive) with the same drawing as the real product, and an accuracy of about 83.1% for a query to a different product (positive: negative). In the future, we plan to conduct a study to improve the matching accuracy between the real product image and the drawing image by combining the parameter optimization study with the proposed model and adding processes such as data purification.

• Journal of Korean Elementary Science Education
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• v.41 no.3
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• pp.538-552
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• 2022

This study attempted to understand the characteristics of pedagogic activities performed by pre-service elementary school teachers. To this end, it applied Algodoo simulations to analyze the actions of students and obtain educational implications for optical learning. The study's participants comprised 79 first-year students enrolled in a teacher training college. Their activities could be classified as representation reproductions, verification experiments, and inquiry experiments. Students who performed representation reproduction exercises replicated renowned and authoritative exemplars, apprehending and demonstrating their principal features through simulations. Students performing verification experiments attempted to validate previously learned optical concepts by reviewing the relevant theoretical contexts. Such students primarily conducted simple experiments. Students accomplishing inquiry experiments used simulations to explore phenomena they did not know. Some of them even investigated optical phenomena beyond the domain of general physics. The above results confirmed that free optical experiments performed using Algodoo can effectively denote starting points for learners to engage in activities at varying levels. Additionally, students require assistance from instructors in addressing queries about the application of the principles and models related to optics. This study suggests ways in which instructors should help students at each level of activity. Additionally, the paper presents examples of varying levels of inquiry-related activities available on Algodoo. It also discusses the advantages and disadvantages of performing inquiry-based activities on Algodoo and suggests ways of enhancing the learning achieved through this platform.