• Journal of KIISE
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• v.42 no.9
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• pp.1109-1116
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• 2015

In this paper, we propose a query processing approach that uses the Spark functional programming and distributed memory system to solve the computational overhead of SPARQL. In the semantic web, RDF ontology data is produced at large scale, and the main challenge for the semantic web is to query and manipulate such a large ontology with a high throughput. The most existing studies on SPARQL have focused on deploying the Hadoop MapReduce framework, and although approaches based on Hadoop MapReduce have shown promising results, they achieve a low level of throughput due to the underlying distributed file processes. Therefore, in order to speed up the query processes, we suggest query- processing methods that are based on memory caching in distributed memory system. Our approach is also integrated with a clause unification method for propagating between the clauses that exploits Spark join, map and filter methods along with caching. In our experiments, we have achieved a high level of performance relative to other approaches. In particular, our performance was nearly similar to that of Sempala, which has been considered to be the fastest query processing system.

• KIPS Transactions on Software and Data Engineering
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• v.2 no.3
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• pp.173-186
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• 2013

Web-based map services provide various geographic information that users want to get by continuous updating of data. Those map services provide different information for a geographic object respectively. It causes several problems, and most of all various information cannot be integrated and provided. To resolve the problem, this paper proposes a system which can integrate diverse geographic information and provide users rich geographic information. In this paper, a hybrid schema matching (HSM) algorithm is proposed and the algorithm is a mixture of the adapter-based semantic processing method, static semantic management-based approach, and dynamic semantic management-based approach. A comparative evaluation is described to show effectiveness of the proposed algorithm. The proposed algorithm in this paper improves the accuracy of schema matching because of registration and management of schemas of new semantic information. The proposal enables vocabulary-based schema matching using various schemas, and it thus also supports high usability. Finally, the proposed algorithm is cost-effective by providing the progressive extension of relationships between schema meanings.

• CONCEPT AND COMMUNICATION
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• no.22
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• pp.241-279
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• 2018

Little research has been done on the relationship between discussions of Munmyeong and Munhwa in early 20th-century Korea. This paper addresses the topic by examining the discussion context of these two keywords and how this changed over the period, using a Language Network Analysis methodology. The study consisted of three stages. First, a corpus was constructed by extracting the context of the keywords from Hwangseong Sinmun and 11 periodicals published during the 1900s, together with Dong-A Ilbo and Gaebyeok from the 1920s. Using this corpus, eight co-occurring word network maps were calculated, each consisting of the 30 words. Second, a semantic spectrum was created by arranging the co-occurring words into 15 categories, to allow comparisons among the co-occurring word network maps. By calculating similarity between these semantic spectra, it was shown that both newspapers and magazines had a high degree of similarity of context for the keywords, with Munmyeong being most similar in the late 1900s and Munhwa in the early 1920s. Third, to facilitate further analysis, semantic network maps were created which express the relationship between semantic spectrum components as links. These maps were calculated by applying the 15 categories to the co-occurring word network maps. A comparison of these semantic network maps reveals that the discussion context of Munmyeong in late 1900s newspapers was significantly replicated in the discussion context of Munhwa in the early 1920s.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.11 no.3
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• pp.1722-1741
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• 2017

Intrusion detection techniques based on virtual machine introspection (VMI) provide high temper-resistance in comparison with traditional in-host anti-virus tools. However, the presence of semantic gap also leads to the performance and compatibility problems. In order to map raw bits of hardware to meaningful information of virtual machine, detailed knowledge of different guest OS is required. In this work, we present VDSM, a lightweight and general approach based on driver separation mechanism: divide semantic view reconstruction into online driver of view generation and offline driver of semantics extraction. We have developed a prototype of VDSM and used it to do intrusion detection on 13 operation systems. The evaluation results show VDSM is effective and practical with a small performance overhead.

• The Journal of Korean Association of Computer Education
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• v.3 no.1
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• pp.177-189
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• 2000

This paper describes the design and implementation of Korean History Web courseware using semantic network in order to build learning environment in the viewpoint of cognitive flexibility theory. The most important thing in design for a courseware using semantic network is to build learning environment. The first step to do this is to analyze learning contents and after that we should define the type of link between learning subjects. We should develope the knowledge map which has the link of each type connected with every learning subject.

• KSII Transactions on Internet and Information Systems (TIIS)
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• v.16 no.2
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• pp.524-543
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• 2022

Correct facade image parsing is essential to the semantic understanding of outdoor scenes. Unfortunately, there are often various occlusions in front of buildings, which fails many existing methods. In this paper, we propose an end-to-end deep network for facade parsing with occlusions. The network learns to decompose an input image into visible and invisible parts by occlusion reasoning. Then, a context aggregation module is proposed to collect nonlocal cues for semantic segmentation of the visible part. In addition, considering the regularity of man-made buildings, a repetitive pattern completion branch is designed to infer the contents in the invisible regions by referring to the visible part. Finally, the parsing map of the input facade image is generated by fusing the results of the visible and invisible results. Experiments on both synthetic and real datasets demonstrate that the proposed method outperforms state-of-the-art methods in parsing facades with occlusions. Moreover, we applied our method in applications of image inpainting and 3D semantic modeling.

• Proceedings of the Korean Information Science Society Conference
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• 2011.06c
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• pp.142-144
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• 2011

In a world in constant changes, more and more devices are producing data and it is indispensable to manage these data. That is why map reduce framework is a solution to manage a large amount of data in a fast and right way. In the other hand semantic web (RDF/OWL) is getting popular and can be a solution to manage data in an efficient way, so that such data can be retrieved and understood by both human and machine. In this paper we describes and analyze some projects that manages RDF with Map-Reduce framework.

• Journal of the Ergonomics Society of Korea
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• v.34 no.6
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• pp.563-581
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• 2015

Objective: This study was conducted to investigate the potential of sematic network analysis for design research. Background: As HCD (Human-Centered Design) was emphasized, lots of design research methodologies were developed and used in order to find user needs. However, it is still difficult to discover users' latent needs. This study suggests the semantic network analysis as a complementary means for design research, and proved its potential through the practical application, which compares multi-screen purchase and usage behaviors between America and China. Method: We conducted an in-depth interview with 32 consumers from USA and China, and analyzed interview texts through semantic network analysis. Cross cultural differences in purchase and usage behaviors were investigated, based on measuring centrality and community modularity of devices, functions, key buying factors and brands. Results: Americans use more services and functions in the multi-screen environment, compared to Chinese. As a device substitutes other devices, traditional boundaries of the devices are disappearing in the USA. Americans consider function to recall Apple, but Chinese consider function, design and brand to recall Apple, Sony and Samsung as an important brand at the time of their purchase. Conclusion: This study shows the potential of semantic network analysis for design research through the practical application. Semantic network analysis presents how the concepts regarding a theme are structured in the cognitive map of users with visual images and quantitative data. Therefore, it can complement the qualitative analysis of the existing design research. Application: As the design environment becomes more and more complicated like multi-screen environment, semantic network analysis, which is able to provide design insights in the intuitive and holistic perspective, will be acknowledged as an effective tool for further design research.

• Journal of the Korean Society for information Management
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• v.29 no.4
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• pp.123-142
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• 2012

To develop an intelligent search engine to help users retrieve information effectively, various methods, such as Semantic Web, have been used, An effective retrieval method of such methods uses ontology technology. In this paper, we built National R&D ontology after analyzing National R&D Information in NTIS and then implemented National R&D Knowledge Map to represent and retrieve information of the relationship between object and subject (project, human information, organization, research result) in R&D Ontology. In the National R&D Knowledge Map, center-node is the object selected by users, node is subject, subject's sub-node is user's favorite query in National R&D ontology after analyzing the relationship between object and subject. When a user selects sub-node, the system displays the results from inference engine after making query by SPARQL in National R&D ontology.

• Journal of the Korean Society of Environmental Restoration Technology
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• v.10 no.1
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• pp.23-35
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• 2007

Nowadays, as a result of increasing income and spare time, the social demands for better living environment become more increasing. Above all, landscape improvement, the essential part of physical environment, will be a more important subject in urban planning. In these circumstances, classification of urban scenic quality is required for urban landscape development programs. The major purpose of this study is to suggest a technical method of designing urban scenic quality map for urban district area based on the scenery management system of the USDA forest service and literature studies. As a conclusion of this study, four steps are desirable for the technical method for designing a scenic quality map of urban districts areas : 1) Define a landscape unit on the map, 2) Take a photograph of these landscape unit on site, 3) Evaluate the landscape unit by semantic differential scale with landscape adjectives, and 4) Draw the scenic quality map, investigate the landscape characteristics and suggest the landscape scenic development plans.