• Journal of Korea Spatial Information System Society
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• v.6 no.2 s.12
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• pp.23-37
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• 2004

Location Based Services(LBSs) in mobile environments become very popular recently. For efficient LBSs, spatial database management systems must need a spatial indexing scheme such as R-trees in order to manage the huge spatial database. However, it may need unnecessary disk accesses since it needs to access objects which are not actually concerned to user's location-based queries. In this paper, to support the location-based queries efficiently, we propose a CLR-tree(Cell Leveling R-tree) in which a dynamic cell is built up within the minimum bounding rectangle of R-trees' node. The cell level of nodes is compared with the query's cell level in location-based query processing and determines the minimum search space. Also, we propose the insertion, split, deletion, and search algorithms for CRL-trees. From the experimental results, we see that a CLR-tree is able to decrease $5{\sim}20%$ of disk accesses from those of R-trees. So, a CLR-tree can be used for fast accessing spatial objects to user's location-based queries in LBSs.

• The Journal of the Korea Contents Association
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• v.10 no.2
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• pp.54-62
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• 2010

Inverted index structures have become the most efficient data structure for high performance indexing of large text collections, especially online index maintenance, In-Place and merge-based index structures are the two main competing strategies for index construction in dynamic search environments. In the above-mentioned two strategies, a contiguity of posting information is the mainstay of design for online index maintenance and query time. Whereas with the emergence of new storage device(SSD, SCRAM), those do not consider a contiguity of posting information in the design of index structures because of its superiority such as low access latency and I/O throughput speeds. However, SSD(Solid State Drive) is not well suited for traditional inverted structures due to the poor random write throughput in practical systems. In this paper, we propose the new efficient online index structure(SPM) for SSD that significantly reduces the query time and improves the index maintenance performance.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2011.10a
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• pp.91-94
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• 2011

The LBSNS(Location-Based Social Networking Service) service has been well-received by researchers and end-users, such as Twitter. Location-Based service of Twitter is now structured that users could not subscribe the information of their interesting local area. Those who being following from someone tweet message included information of local area to them just for their own interesting. However, follower may receive that kind of tweet. In order to handle the problem, we propose filtering technique using spatial join. The first work for filtering technique is to add a location information to tweets and users. In this paper, location information is represented by MBR(Minimum Bounding Rectangle). Location information is divided into dynamic property and static property. Suppose that users are continuously moving, that means one of the dynamic property's example. At this time, a massive continous query could cause the problem in server. In this paper, we create Virtual Grid on Google Map for reducing frequency of query, and conclude that it is useful for server.

• Journal of the Korea Institute of Information Security & Cryptology
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• v.18 no.5
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• pp.135-148
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• 2008

The expansion of the internet has made web applications become a part of everyday lift. As a result the number of incidents which exploit web application vulnerabilities are increasing. A large percentage of these incidents are SQL Injection attacks which are a serious security threat to databases with potentially sensitive information. Therefore, much research has been done to detect and prevent these attacks and it resulted in a decline of SQL Injection attacks. However, there are still methods to bypass them and these methods are too complex to implement in real web applications. This paper proposes a simple and effective SQL Query attribute value removal method which uses Static and Dynamic Analysis and evaluates the efficiency through various experiments.

• Journal of KIISE:Databases
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• v.30 no.5
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• pp.451-463
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• 2003

Recently, there have been various research efforts to develop strategies for accelerating OLAP operations on huge amounts of spatio-temporal data. Most of the work is based on multi-tree structures which consist of a single R-tree variant for spatial dimension and numerous B-trees for temporal dimension. The multi~tree based frameworks, however, are hardly applicable to spatio-temporal OLAP in practice, due mainly to high management cost and low query efficiency. To overcome the limitations of such multi-tree based frameworks, we propose a new approach called Hilbert Cube(H-Cube), which employs fractals in order to impose a total-order on cells. In addition, the H-Cube takes advantage of the traditional Prefix-sum approach to improve Query efficiency significantly. The H-Cube partitions an embedding space into a set of cells which are clustered on disk by Hilbert ordering, and then composes a cube by arranging the grid cells in a chronological order. The H-Cube refines cells adaptively to handle regional data skew, which may change its locations over time. The H-Cube is an adaptive, total-ordered and prefix-summed cube for spatio-temporal data warehouses. Our approach focuses on indexing dynamic point objects in static spatial dimensions. Through the extensive performance studies, we observed that The H-Cube consumed at most 20% of the space required by multi-tree based frameworks, and achieved higher query performance compared with multi-tree structures.

• Journal of KIISE:Databases
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• v.34 no.4
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• pp.315-327
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• 2007

The performance of database applications with large sets of multidimensional data depends on the performance of its access methods and the underlying disk system. In modeling the disk system, even though modem disks are manufactured with multiple physical zones, conventional access methods have been developed based on a traditional disk model with many simplifying assumptions. Thus, there is a marked lack of investigation on how to enhance the performance of access methods given a zoned disk model. The paper proposes novel zoning techniques that can be applied to any multidimensional access methods, both static and dynamic, enhancing the effective data transfer rate of underlying disk system by fully utilizing its zone characteristics. Our zoning techniques include data placement algorithms for multidimensional index structures and accompanying localized query processing algorithms for range queries. The experimental results show that our zoning techniques significantly improve the query performance.

• Journal of Korea Multimedia Society
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• v.10 no.11
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• pp.1398-1406
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• 2007

Providing natural and efficient access to the fast growing multimedia information is a critical aspect for content-based information system. Query by humming system allows the user to find a song by humming part of the tune form music database. Conventional music information retrieval systems use a high precision pitch extraction method. However, it is very difficult to extract true pitch perfectly. So, In this paper, we propose to use YIN parameter with applying the reliability to reduce the pitch extraction errors. And we describes developed music information retrieval method based on a query by humming system which uses reliable feature extraction. Developed system is based on a continuous dynamic programming algorithm with features including pitch, duration and energy along with their confidence measures. The experiment showed that the proposed method could reduce the errors of the top-10 7.2% and the top-1 9.1% compared with the cepsturm based multiple pitch candidate. The overall retrieval system achieved 92.8% correct retrieval in the top-10 rank list on a database of 155 songs.

• The Transactions of the Korea Information Processing Society
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• v.6 no.11
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• pp.2911-2921
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• 1999

We present new methods for an efficient retrieval of SGML documents. We define IDDL (index database description language) which is able to describe various information such as meta data, an indexing range, and the creation and manipulation of a database. In addition, we design IDQL (index database query language) that can deal with querying meta data as well as logical structure. Especially, the retrieval system based on IDDL and IDQL has been developed and implemented, and has been experimented on large number of documents. Experimental result shows that the proposed method provides the dynamic creation of an index database and a convenient retrieval environment.

• Journal of Intelligence and Information Systems
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• v.7 no.1
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• pp.47-61
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• 2001

Lazy loaming methods including CBR have relative advantages in comparison with eager loaming methods such as artificial neural networks and decision trees. However, they are very sensitive to irrelevant features. In other words, when there are irrelevant features, larry learning methods have difficulty in comparing cases. Therefore, their performance can be degraded significantly. To overcome this disadvantage, feature weighting methods for lazy loaming methods have been studied. Most of the existing researches, however, were focused on global feature weighting. In this research, we propose a new local feature weighting method, which we shall call CBDFW. CBDFW stores classification performance of randomly generated feature weight vectors. Then, given a new query case, CBDFW retrieves the successful feature weight vectors and designs a feature weight vector fur the query case. In the test on credit evaluation domain, CBDFW showed better classification accuracy when compared to the results of previous researches.

• The KIPS Transactions:PartD
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• v.13D no.1 s.104
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• pp.29-36
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• 2006

In this paper, we present a leaf image retrieval system that represents and retrieves leaf images based on their shape. For more effective representation of leaf images, we improved an existing MPP algorithm. Also, in order to reduce the response time, we proposed a new dynamic matching algorithm at basically revises the Nearest Neighbor search. The system provides users with an interface for uploading query images or tools to generate queries based on shape features and retrieves images based on their similarity. For convenience, users are allowed to easily query images by sketching leaf shape or leaf arrangement on the web. In the experiment, we constructed an image database of Korean native plants and measured the system performance by counting the number of similar images retrieved for queries.