• Journal of KIISE:Databases
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• v.30 no.3
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• pp.252-272
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• 2003

The view mechanism provides users with appropriate portions of database through data filtering and integration. In the Web era where information proliferates, the view concept is also useful for XML, a future standard for data exchange on the Web. This paper proposes a method of implementing XML views called XML view indexing, whereby XML view xv is represented as an XML view index(XVI) which is a structure containing the identifiers of xv's underlying XML elements as well as the information on xv. Since XVI for xv stores just the identifiers of the XML elements but not the elements themselves, when a user requests to retrieve xv, its XVI should be materialized against xv's underlying XML documents. Also an efficient algorithm to incrementally maintain consistency of XVI given a update of xv's underlying XML documents is required. This paper proposes and implements data structures and algorithms for XML view indexing. The performance experiments on XML view indexing reveal that it outperforms view recomputation for repeated accesses to the view, and requires as much as about 30 times less storage space compared to XML view materialization though the latter takes less time for repeated accesses to the view due to no need of materialization.

• Journal of KIISE:Databases
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• v.31 no.4
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• pp.341-351
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• 2004

With the popularity of digital audio contents, querying and retrieving audio contents efficiently from database has become essential. In this paper, we propose a new index scheme for retrieving audio contents efficiently using audio portions that have been queried frequently. This scheme is based on the observation that users have a tendency to memorize and query a small number of audio portions. Detecting and indexing such portions enables fast retrieval and shows better performance than sequential search-based audio retrieval. Moreover, this scheme is independent of underlying retrieval system, which means this scheme can work together with any other audio retrieval system. We have implemented a prototype system and showed its performance gain through experiments.

• Journal of KIISE:Databases
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• v.31 no.1
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• pp.72-81
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• 2004

Theses days, a number of data over the Internet are represented using XML because of a virtue of XML. In proportion to the increase of XML data, query processing techniques are required that support quickly and efficiently the diverse queries to search the useful information on XML documents. But, up to now, the researches handling queries for XML data are methodologies focusing on how to process regular path expressions. Therefore, we have developed a new genealogy-based indexing technique to solve various queries such as not only regular path expression but also simple path expression, path expression referencing other elements, and so on. Also, we have applied this technique on object-relational model and evaluated the performance for many documents and various query types. The result shows improved performance in comparison with the other storage techniques.

• Spatial Information Research
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• v.6 no.2
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• pp.125-132
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• 1998

The I/O performance for spatial queries is extremely important since the handling of huge amount of multidimensional data is required in spatial databases for geographic information systems. Therefore, we describe representative spatial access methods handling complex spatial objects, z-transform B tree, KDB tree, R tree, MAX tree, to increase I/O performance. In addition, we measure the performance of spatial indexing schemes by testing against various realistic data and query sets. Results from the benchmark test indicates that MAX outperforms other indexing schemes on insertion, range query, spatial join. MAX tree is expected to use as index scheme organizing storage system of GIS in the future.

• Convergence Security Journal
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• v.8 no.4
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• pp.97-104
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• 2008

Recently, the wireless positioning techniques and mobile computing techniques have rapidly developed to use location data of moving objects. The more the number of moving objects is numerous and the more periodical sampling of locations is frequent, the more location data of moving objects become very large. Hence the system should be able to efficiently manage mass location data, support various spatio-temporal queries for LBS, and solve the uncertainty problem of moving objects. Therefore, in this paper, innovating the location data of moving object effectively, we propose Rend 3DR-tree method to decrease the dead space and complement the overlapping of nodes by utilizing 3DR-tree with the indexing structure to support indexing of current data and history data.

• The Transactions of the Korea Information Processing Society
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• v.3 no.3
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• pp.655-671
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• 1996

Using object relationship table, this study proposes an efficient indexing technique for accessing both aggregation and inheritance hierarchies in object- oriented databases. This indexing technique uses the information on the aggregation and inheritance relationship between classes and the information on referencing instances as meta data. As a result, the technique makes it possible to effectively evaluates various queries navigating between tables. The study compares the proposed technique with the existing indexing techniques and discusses its useful- ness. It also provides the result of simulating its performance in terms of storage and retrieval cost.

• Proceedings of the IEEK Conference
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• 2003.07d
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• pp.1527-1530
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• 2003

Video is an important and challenge media and requires sophisticated indexing schemes for efficient retrieval from visual databases. Scene change detection is the first step for automatic indexing of video data. Recently, several scene change detection algorithms in the pixel and compressed domains have been reported in the literature. However, using pixel methods are computationally complex and are not very robust in detecting scene change detection. In this paper, we propose robust abrupt scene change detection using macroblock type and DC coefficient. Experimental results show that the proposed algorithm is robust for detection of most abrupt scene changes in the compressed domain.

• The Journal of Society for e-Business Studies
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• v.13 no.4
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• pp.209-222
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• 2008

The product information can be practically stored and managed, and also queried when we use a relational database. We need to develop a special indexing scheme in order to process the queries to ask for the semantic relationships of the product information. Such semantic relationships include ISA or taxonomy relationships that have the transitive properties. In this paper, we propose an index scheme to effectively process those queries with the transitive property. The proposed index scheme is based on a numbering scheme that has relatively low update cost.

• Journal of the Institute of Convergence Signal Processing
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• v.7 no.1
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• pp.11-16
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• 2006

To manipulate large video databases, effective video indexing and retrieval are required. A large number of video indexing and retrieval algorithms have been presented for frame-w]so user query or video content query whereas a relatively few video sequence matching algorithms have been proposed for video sequence query. In this paper, we propose an efficient algorithm to extract key frames using color histograms and to match the video sequences using edge features. To effectively match video sequences with low computational load, we make use of the key frames extracted by the cumulative measure and the distance between key frames, and compare two sets of key frames using the modified Hausdorff distance. Experimental results with several real sequences show that the proposed video retrieval algorithm using color and edge features yields the higher accuracy and performance than conventional methods such as histogram difference, Euclidean metric, Battachaya distance, and directed divergence methods.

• The Journal of Information Systems
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• v.14 no.3
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• pp.37-47
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• 2005

Mining of association rules is to find associations among data items that appear together in some transactions or business activities. As of today, algorithms for association rule mining, as well as for other data mining tasks, are mostly applied to relational databases. As XML being adopted as the universal format for data storage and exchange, mining associations from XML data becomes an area of attention for researchers and developers. The challenge is that the semi-structured data format in XML is not directly suitable for traditional data mining algorithms and tools. In this paper we present an encoding method to encode XML tree-nodes. This method is used to store the XML data in Value Table and Transaction Table that can be easily accessed via indexing. The hierarchical relationship in the original XML tree structure is embedded in the encoding. We applied this method to association rules mining of XML data that may have missing data.