• Journal of KIISE:Databases
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• v.35 no.6
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• pp.495-504
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• 2008

Recently, there has been much work on supporting keyword search not only for text documents, but a]so for structured data such as relational data, XML data, and RDF data. In this paper, we propose an efficient keyword search method for RDF data. The proposed method first groups related nodes and edges in RDF data graphs to reduce data sizes for efficient keyword search and to allow relevant information to be returned together in the query answers. The proposed method also utilizes the semantics in RDF data to measure the relevancy of nodes and edges with respect to keywords for search result ranking. The experimental results based on real RDF data show that the proposed method reduces RDF data about in half and is at most 5 times faster than the previous methods.

• The Journal of Society for e-Business Studies
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• v.12 no.3
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• pp.251-268
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• 2007

We design and implement an efficient storage technique to improve query processing for a large RDF data set. The proposed techniques can minimize data redundancy compared to the existing techniques by splitting relation information and data information from triple formatted RDF data. Also, we can enhance query processing speed separating and connecting the entire query steps by relation and data based on the proposed storage technique. The proposed technique can be applied to the areas, such as e-Commerce, semantic web, and KMS to store and retrieve a large RDF data set.

• Journal of KIISE
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• v.41 no.12
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• pp.1126-1135
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• 2014

In recent years, RDF partitioning schemes have been studied for the effective distributed storage and management of large-scale RDF data. In this paper, we propose an RDF dynamic partitioning scheme to support load balancing in dynamic environments where the RDF data is continuously inserted and updated. The proposed scheme creates clusters and sub-clusters according to the frequency of the RDF data used by queries to set graph partitioning criteria. We partition the created clusters and sub-clusters by considering the workloads and data sizes for the servers. Therefore, we resolve the data concentration of a specific server, resulting from the continuous insertion and update of the RDF data, in such a way that the load is distributed among servers in dynamic environments. It is shown through performance evaluation that the proposed scheme significantly improves the query processing time over the existing scheme.

• The Journal of the Korea Contents Association
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• v.5 no.6
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• pp.1-9
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• 2005

As the amount of data on the web increase, it is difficult to search what we want exactly. Therefore, much researches are attempted to search web resources efficiently. So, W3C established the standard that give meanings to resources on the web using RDF metadata. The RDF metadata had been mainly described a document data on the web. But it is difficult to create automatically the metadata for application programs than the document data. This paper proposes a method to use RDF metadata to search application programs. Firstly, we define RDF data model that stores the information of the application programs and RDF schema that references the RDF data model. And we design a prototype system to search application programs. This system meets expectation, getting the application to fullfill the needs of user, and has the efficiency of the searching function.

• Journal of Korean Library and Information Science Society
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• v.48 no.3
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• pp.233-257
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• 2017

In this paper, we propose an effective method to convert and construct the MEDLINE, the world's largest biomedical bibliographic database, into linked data. To do this, we first derive the appropriate RDF schema by analyzing the MEDLINE record structure in detail, and convert each record into a valid RDF file in the derived schema. We apply the dual batch registration method to streamline the subject URI duplication checking procedure when merging all RDF files in the converted record unit and storing it in a single RDF triple storage. By applying this method, the number of RDF triple storage accesses for the subject URI duplication is reduced from 26,597,850 to 2,400, compared with the sequential configuration of linked data in units of RDF files. Therefore, it is expected that the result of this study will provide an important opportunity to eliminate the inefficiency in converting large volume bibliographic record sets into linked data, and to secure promptness and timeliness.

• The Journal of The Korea Institute of Intelligent Transport Systems
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• v.20 no.6
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• pp.110-116
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• 2021

W3C enacted RDF(Resource Description Framework based DCAT meta data standard, which is world-widely accepted so far. To guarantee the inter-operability and integrity of data from various sources and even from various countries, it is considered that transportation meta data should also follow the DCAT standard. But still, to represent the transportation domain-specific features, it is necessary to define new properties and vocabularies in addition to the DCAT standard. This research identified the additional properties and vocabularies for transportation metadata, considering uniqueness of transportation data. The revised RDF schema and RDF graph proposed in this research should be able to lead the transportation open data platform revitalization.

• Journal of Korean Library and Information Science Society
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• v.37 no.3
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• pp.415-431
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• 2006

The semantic web was proposed as the next generation web technology. In the environment of the semantic web, resources as well defined and related with each other semantically, the RDF supports this basic mechanism. To establish and develop the semantic web. the basic technologies related to RDF data must be pre-established. In this research, we develop methods for storing and querying RDF data using an XML database system. As using XML database, XML data and RDF data can be integrated and efficiently managed. We construct and evaluate a system applying the proposed method to store and search data, we compared the query processing performance on our system with that of an existing system. The experiment result show that our system processes queries more efficiently.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.26 no.4
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• pp.487-494
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• 2022

With the recent demand for analysis using data, the size of the knowledge graph, which is the data to be analyzed, gradually increased, reaching about 82 billion edges when extracted from the web as a knowledge graph. A lot of knowledge graphs are represented in the form of Resource Description Framework (RDF), which is a standard of W3C for representing metadata for web resources. Because of the characteristics of RDF, existing RDF storages have the limitations of processing time overhead when converting and storing large amounts of RDF data. To resolve these limitations, in this paper, we propose a method of compressing and converting large amounts of RDF data into integer IDs using MapReduce, and vertically partitioning and storing them. Our proposed method demonstrated a high performance improvement of up to 25.2 times compared to RDF-3X and up to 3.7 times compared to H2RDF+.

• Journal of KIISE:Databases
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• v.31 no.2
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• pp.195-204
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• 2004

The Semantic Web is proposed as the next generation Web technology. In the environment of the Semantic Web, resources are related with each other semantically and computers can process this information easily. The Resource Description Framework (RDF) supports this semantic relationship. RDF is the data model for describing metadata of the Web resources. To establish and develop the Semantic Web, methods for managing RDF data efficiently are the most important. So, in this research, we propose methods for storing and querying RDF data using an XML database system. Using an XML database system, XML data, main data of the Semantic Web, and RDF data, the metadata of XML data, can be managed in the same storage and by the same mechanism efficiently. In addition, we propose an efficient data retrieval method and several techniques to improve the system performance. Our query processing technique performs better than an existing system.

• KIPS Transactions on Software and Data Engineering
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• v.3 no.1
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• pp.19-30
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• 2014

For the expansion of the Semantic Web, studies in converting the data stored in the relational database into the ontology are actively in process. Such studies mainly use an RDB to RDF mapping model, the model to map relational database components to RDF components. However, pre-proposed mapping models have got different expression modes and these damage the accessibility and reusability of the users. As a consequence, the necessity of the standardized mapping language was raised and the W3C suggested the R2RML as the standard mapping language for the RDB to RDF model. The R2RML has a characteristic that converts only the relational database schema data to RDF. For the same reasons above, the ontology about the relation data between table name and column name of the relational database cannot be added. In this paper, we propose an RDB to RDF mapping system considering semantic relations of RDB components in order to solve the above issue. The proposed system generates the mapping data by adding the RDFS attribute data into the schema data defined by the R2RML in the relational database. This mapping data converts the data stored in the relational database into RDF which includes the RDFS attribute data. In this paper, we implement the proposed system as a Java-based prototype, perform the experiment which converts the data stored in the relational database into RDF for the comparison evaluation purpose and compare the results against D2RQ, RDBToOnto and Morph. The proposed system expresses semantic relations which has richer converted ontology than any other studies and shows the best performance in data conversion time.