• Journal of KIISE:Databases
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• v.29 no.1
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• pp.1-14
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• 2002

Association rule discovery is a method of mining for the associated item set on large databases based on support and confidence threshold. The discovered association rules can be applied to the marketing pattern analysis in E-commerce, large shopping mall and so on. The association rule discovery makes multiple scan over the database storing large transaction data, thus, the algorithm requiring very high overhead might not be useful in real-time association rule discovery in dynamic environment. Therefore this paper proposes an active candidate set management model based on trigger and incremental update mechanism to overcome non-realtime limitation of association rule discovery. In order to implement the proposed model, we not only describe an implementation model for incremental updating operation, but also evaluate the performance characteristics of this model through the experiment.

• The Journal of Korean Institute of Communications and Information Sciences
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• v.35 no.11C
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• pp.929-939
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• 2010

The growth of multimedia technology forces the development of video detection for large database management and illegal copy detection. To meet this demand, this paper proposes a fast video detection method to apply to a large database. The fast video detection algorithm uses spatial features using the gray value distribution from frames and temporal features using the temporal similarity map. We form the video signature using the extracted spatial feature and temporal feature, and carry out a stepwise matching method. The performance was evaluated by accuracy, extraction and matching time, and signature size using the original videos and their modified versions such as brightness change, lossy compression, text/logo overlay. We show empirical parameter selection and the experimental results for the simple matching method using only spatial feature and compare the results with existing algorithms. According to the experimental results, the proposed method has good performance in accuracy, processing time, and signature size. Therefore, the proposed fast detection algorithm is suitable for video detection with the large database.

• Journal of the Korean Institute of Telematics and Electronics T
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• v.35T no.2
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• pp.81-85
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• 1998

Location Registration and deregistration is necessary to mobility management in a Mobile Communication networks when a mobile phone moves between location registration areas. After considering several deregistration schemes, a sample scheme that eliminate network traffic is chosen. However, this scheme may delete valid registration record, so the size of location registration database must be sufficiently large to ensure low probability that a valid records are deleted. This paper describes an analytic model to determine the size of location registration database for a location registration area in this simple scheme. The simulation results of analytic model show that the size of database must 3-5 times than the expected number of mobile phones in a location registration area.(Mobile, Communications, Location, Deregistration, Database)

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2003.09b
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• pp.49-52
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• 2003

In this research, we propose a mechanism to develop an inference engine and expert systems based on relational database and SQL (structured query language). Generally, former researchers had tried to develop an expert systems based on text-oriented knowledge base and backward/forward (chaining) inference engine. In these researches, however, the speed of inference was remained as a tackling point in the development of agile expert systems. Especially, the forward inference needs more times than backward inference. In addition, the size of knowledge base, complicate knowledge expression method, expansibility of knowledge base, and hierarchies among rules are the critical limitations to develop an expert systems. To overcome the limitations in speed of inference and expansibility of knowledge base, we proposed a relational database-oriented knowledge base and forward inference engine. Therefore, our proposed mechanism could manipulate the huge size of knowledge base efficiently, and inference with the large scaled knowledge base in a short time. To this purpose, we designed and developed an SQL-based forward inference engine using relational database. In the implementation process, we also developed a prototype expert system and presented a real-world validation data set collected from medical diagnosis field.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.26 no.1
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• pp.125-134
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• 2016

MySQL database is currently used by many users and It has gained a big market share in the database market. Even though MyISAM storage engine was used as a default storage engine before, but records recovery method does not existed. Deleted records have a high possibility for important evidence and it is almost impossible to determine that investigators manually examine large amounts of database directly. This paper suggests the universal recovery method for deleted records and presents the experimental results.

• Journal of Internet Computing and Services
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• v.2 no.5
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• pp.41-47
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• 2001

This paper deals with an EJB-based database agent(component) used to define workflow processes, which is a core function of the e-Chautauqua workflow management system that is an on-going research product. We describe about how to design and implement the EJB-based DB agent that is deployed on EJB server as a component. The agent is located between the build-time clients and the database system, and manages database accesses, such as retrieves and stores, from the workflow definition components. Through the EJB technology, we are able to accomplish a stable database agent that can be characterized by the distributed object management, reliable recovery mechanism from system failovers, reliable large-scale transaction management, and the security functions.

• Korean Journal of Cognitive Science
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• v.13 no.1
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• pp.41-51
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• 2002

In this paper, I describe a knowledge-based question-answering system and significance of the system with a view to constructing a fact database. The knowledge-based system takes advantage of existing NLP-resources such as conceptual structures of ontologies along with morphotogical, syntactic and semantic analysis. The use of conceptual structures allows us to select right answers through inferences basically made by expansions of concepts. However, the work of constructing factual knowledge requires a great amount of acquisition time in large-scale applications because of the nature of human interference. This is why the procedure of acquiring factual knowledge cannot be fully automated. Apart from efficiency considerations. the knowledge-based system deserves serious consideration, I point out benefits of the system and describe the whole procedure of building the system in terms of a fact database.

• Proceedings of the KSRS Conference
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• 2004.10a
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• pp.99-102
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• 2004

Recently according to developing of bioinformatics techniques, there are a lot of researches about large amount of biological data. And a variety of files and databases are being used to manage these data efficiently. However, because of the deficiency of standardization there are a lot of problems to manage the data and transform one into the other among heterogeneous formats. We are interested in integrating. saving, and managing gene and protein sequence data generated through sequencing. Accordingly, in this paper the goal of our research is to implement the system to manage sequence data and transform a sequence file format into other format. To satisfy these requirements, we adopt BSML (Bioinformatics Sequence Markup Language) as the standard to manage the bioinformatics data. And then we integrate and store the heterogeneous 리at file formats using BSML schema based DTD. And we developed the system to apply the characteristics of object-oriented database and to process XPath query, one of the efficient structural query. that saves and manages XML documents easily.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2008.10a
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• pp.139-142
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• 2008

While a lot of comparisons of DBMS performance for processing large scale database are given as results of bench-mark tests, there are few comparisons of DBMS performance for processing small scale database. Therefore, in this study, we compared and analyzed on the performance of commercial DBMS and public DBMS for small scale database. Analysis results show that while Oracle has low performance on the operations of update and insert due to the overhead of rollback for data safety, MySQL and MS-SQL have good performance without additional overhead.

• 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.