• Journal of KIISE:Databases
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• v.30 no.1
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• pp.27-40
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• 2003

The inverted index widely used in the existing information retrieval field should be extended for XML documents to support containment queries by XML information retrieval systems. In this paper, we consider that there are two methods in storing the inverted index and processing containment queries for XML documents as the previous work suggested: using a RDBMS or using an inverted lift engine. It has two drawbacks to extend the inverted index in the previous work. One is that using a RDBMS is moth worse in the performance than using an inverted list engine. The other is that when containment queries are processed in a RDBMS, there is an increase in the number of a join operation as the path length of a query increases and a join operation always happens between large fables. In this paper. we extend the inverted index in a different way to solve these problems and show the effectiveness of using a RDBMS.

• Journal of the Korea Institute of Information and Communication Engineering
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• v.21 no.11
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• pp.2067-2075
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• 2017

Lately big data processing is considered as an emerging issue. As a huge amount of data is generated, data processing capability is getting important. In processing big data, both Hadoop distributed file system and unstructured date processing-based NoSQL data store are getting a lot of attention. However, there still exists problems and inconvenience to use NoSQL. In case of low volume data, MapReduce of NoSQL normally consumes unnecessary processing time and requires relatively much more data retrieval time than RDBMS. In order to address the NoSQL problem, in this paper, an interworking scheme between NoSQL and the conventional RDBMS is proposed. The developed auto-mapping scheme enables to choose an appropriate database (NoSQL or RDBMS) depending on the amount of data, which results in fast search time. The experimental results for a specific data set shows that the database interworking scheme reduces data searching time by 35% at the maximum.

• Journal of KIISE:Databases
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• v.35 no.4
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• pp.333-344
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• 2008

In recent years, the web services composition has received much attention. By web services composition, we mean providing a new service that does not exist on the repository. In this paper, we propose a new system called PSR for web services composition search using a relational database. We also propose algorithms for pre-computing web services composition using joins and indices. We store ontologies from web services in RDBMS, so that the PSR system returns web services composition in order of similarity with user query through the degree of the ontology matching. We demonstrated that our pre-computing web services composition approach in RDBMS yields lower execution time and good scalability when handling a large number of web services and user queries.

• Journal of Korea Multimedia Society
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• v.9 no.12
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• pp.1552-1559
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• 2006

In a web environment, similar information exists in many different places in diverse formats. Even duplicate information is stored in the various databases using different terminologies. Since most information serviced in the current World Wide Web however had been constructed before the advent of ontology, it is practically almost impossible to construct ontology for all those resources in the web. In this paper, we assume that most information in the web environment exist in the form of RDBMS, and propose a matching method between domain ontology and existing RDBMS tables for semantic retrieval. In the processing of extracting a local ontology, some problems such as losing domain in formation can occur since the correlation of domain ontology has not been considered at all. To prevent these problems, we propose an instance-based matching which uses relational information between RDBMS tables and relational information between classes in domain ontology. To verify the efficiency of the method proposed in this paper, several experiments are conducted using the digital heritage information currently serviced in the countrywide museums. Results show that the proposed method increase retrieval accuracy in terms of user relevance and satisfaction.

• Journal of Information Processing Systems
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• v.10 no.3
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• pp.355-364
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• 2014

Internet accessibility has been growing due to the diffusion of smartphones in today's society. Therefore, people can generate data anywhere and are confronted with the challenge that they should process a large amount of data. Since the appearance of relational database management system (RDBMS), most of the recent information systems are built by utilizing it. RDBMS uses foreign-keys to avoid data duplication. The transactions in the database use attributes, such as atomicity, consistency, isolation, durability (ACID), which ensures that data integrity and processing results are stably managed. The characteristic of RDBMS is that there is high data reliability. However, this results in performance degradation. Meanwhile, from among these information systems, some systems only require high-performance rather than high reliability. In this case, if we only consider performance, the use of NoSQL provides many advantages. It is possible to reduce the maintenance cost of the information system that continues to increase in the use of open source software based NoSQL. And has a huge advantage that is easy to use NoSQL. Therefore, in this study, we prove that the leverage of NoSQL will ensure high performance than RDBMS by applying NoSQL to database systems that implement RDBMS.

• Proceedings of the Korean Information Science Society Conference
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• 2004.04b
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• pp.214-216
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• 2004

XML 문서에 대한 데이터의 통계 정보는 XML 어플리케이션에 유용하다. 특히 XML 어플리케이션에 대해 RDBMS 테이블 형U로 유도하는 방법 중 cost-based approach를 적용할 때 다양한 Schema 변환 중 어플리케이션에 가장 적합한 것을 선택하는 데 사용한다. 본 논문에서는 정차한 통계 정보를 모으기 위해 Shared type과 변환 과정에 생기는 잠재적인 Shared type에 대해 해결한 X2R System을 개발하였고. 효율적으로 통계를 유지하도록 하였다.

• Journal of Korea Multimedia Society
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• v.21 no.8
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• pp.934-941
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• 2018

There are some limits on cost and efficiency for large amount of data in RDBMS, and NoSQL is starting to gain popularity. In medical institutions, data forms are different between organizations, and that makes difficulty for interoperability between organizations. In this paper we focused on performance issues between RDMBS and NoSQL in medical documents. We had built two different environment and had experiment comparative analysis of NoSQL with RDBMS based on medical data. We used medical HL7 FHIR as a medical data standard. Also YCSB benchmark tool was used for performance comparison. Experiments shows that NoSQL has better performance in large amounts of medical data processing systems that have over 10,000~100,000 records.

• Digital Contents
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• no.4 s.47
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• pp.5-11
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• 1997

관계형 데이터베이스관리시스템(이하 RDBMS)업계에 객체관계형 DBMS(이하 ORDBMS) 열풍이 몰아치고 있다. 지난해 인포믹스와 오라클의 유니버설 논쟁으로 시작된 ORDB 논쟁은 올들어 주요 RDBMS 업체들이 잇달아 ORDBMS 제품을 내놓거나 출시를 앞두고 있어 본격적인 시장경쟁으로 이어질 전망이다. DBMS 시장의 이같은 급속한 변화는 실상 인터넷 붐이 만들어 낸 또다른 현상이라고 해도 과언이 아니다. 인터넷의 속성상 데이터만이 아니라 비정형 멀티미디어 데이터를 처리할 수 있는 새로운 개념의 데이터베이스 관리시스템이 필요하기 때문이다. 지난 93년 유니SQL 공급을 시발로 시작된 국내 ORDBMS 시장은 지난해 일러스트라 공급과 인포믹스 유니버설 서버 발표로 시장형성기에 접어들었으며, 올 하반기면 주요 RDBMS 업체들이 모두 제품을 출시할 것으로 보여 본격적인 개화기에 접어들 것으로 보인다. 국내 주요 RDBMS 업체를 중심으로 변화하는 DBMS 시장과 ORDBMS 전략을 점검해 본다.

• Proceedings of the Korea Information Processing Society Conference
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• 2015.10a
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• pp.234-237
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• 2015

현재 RDBMS는 대부분 블록기반의 스토리지를 사용하는데 오늘날 정형화 되지 않은 데이터 타입에 대한 요청이 많아지고 있어서 오브젝트 스토리지를 사용하려는 연구가 활발히 진행 되고 있다. 그래서 본 논문을 통해 오브젝트 스토리지를 사용하는 RDBMS 환경을 제안한다. 오브젝트 스토리지 중 오픈 소스로 많이 사용되고 있는 Swift와 Ceph를 사용하여 시스템을 구축, 두 시스템간의 파일 및 RDBMS 성능비교를 진행하였다. Swift와 Ceph는 동일한 인터페이스가 아니기에 중간에 새로운 레이어를 추가하여 POSIX 환경에서 테스트가 가능하도록 하였다. 데이터베이스는 Postgresql을 사용하였고 두 시스템 간의 성능측정은 파일벤치마크인 IOzone 그리고 Posgresql에서 지원하는 TPC-B 기반 pgbench를 사용, 노드 확장성과 가상 클라이언트 수를 비교표로 활용하여 실험을 진행하였다.

• Journal of KIISE:Databases
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• v.36 no.4
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• pp.247-253
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• 2009

Rank learning and processing have gained much attention in the IR and data mining communities for the last decade. While other data mining techniques such as classification and regression have been actively researched to interoperate with RDBMS by using the tightly coupled or loose coupling approaches, ranking has been researched independently without integrating into RDBMS. This paper proposes a tightly coupled integration of the Ranking SVM into MySQL in order to perform the rank learning task efficiently within the RDBMS. We implemented new SQL commands for learning ranking functions and predicting ranking scores. We evaluated our tightly coupled integration of Ranking SVM by comparing it to a loose coupling implementation. The experiment results show that our approach has a performance improvement of $10{\sim}40%$ in the training phase and 60% in the prediction phase.