• The KIPS Transactions:PartD
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• v.14D no.2
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• pp.157-168
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• 2007

For effective analyses in various business applications, OLAP(On-Line Analytical Processing) systems represent the multidimensional data as the horizontal format of tables whose columns are corresponding to values of dimension attributes. Because the traditional RDBMSs have the limitation on the maximum number of attributes in table columns(MS SQLServer and Oracle permit each table to have up to 1,024 columns), horizontal tables cannot be directly stored into relational database systems. In this paper, we propose various efficient optimization strategies in transforming horizontal queries to equivalent vertical queries. To achieve this goral, we first store a horizontal table using an equivalent vertical table, and then develop various query transformation rules for horizontal table queries using the PIVOT operator. In particular, we propose various alternative query transformation rules for the basic relational operators, selection, projection, and join. Here, we note that the transformed queries can be executed in several ways, and their execution times will differ from each other. Thus, we propose various optimization strategies that transform the horizontal queries to the equivalent vertical queries when using the PIVOT operator. Finally, we evaluate these methods through extensive experiments and identify the optimal transformation strategy when using the PIVOT operator.

• Journal of KIISE:Databases
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• v.31 no.6
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• pp.641-649
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• 2004

The relationship between chemical structures and biological activities is researched briskly in the area of 'Medicinal Chemistry' At the base of these structure-based drug design tries, medicinal chemists search the existing drugs of similar chemical structure to target drug for the development of a new drug. Therefore, it is such necessary that an automatic system selects drug files that have a set of chemical moieties matching a user-defined query moiety. Substructure searching is the process of identifying a set of chemical moieties that match a specific query moiety. Testing for substructure searching was developed in the late 1950s. In graph theoretical terms, this problem corresponds to determining which graphs in a set are subgraph isomorphic to a specified query moiety. Testing for subgraph isomorphism has been proved, in the general case, to be an NP- complete problem. For the purpose of overcoming this difficulty, there were computational approaches. On the 1990s, a US patent has been granted on an atom-centered indexing scheme, used by the RS3 system; this has the virtue that the indexes generated can be searched by direct text comparison. This system is commercially used(http://www.acelrys.com/rs3). We define the RS3 system's drawback and present a new indexing scheme. The RS3 system treats substructure searching with substring matching by means of expressing chemical structure aspredefined strings. However, it has insufficient 'rerall' and 'precision‘ because it is impossible to index structures uniquely for same atom and same bond. To resolve this problem, we make the minimum-cost- spanning tree for one centered atom and describe a structure with paths per levels. Expressing 2D chemical structure into 1D a string has limit. Therefore, we break 2D chemical structure into 1D structure fragments. We present in this paper a new index technique to improve recall and precision surprisingly.

• The KIPS Transactions:PartD
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• v.16D no.4
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• pp.463-474
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• 2009

To analyze multidimensional data conveniently and efficiently, OLAP (On-Line Analytical Processing) systems or e-business are widely using views in a horizontal form to represent measurement values over multiple dimensions. These views can be stored as materialized views derived from several sources in order to support accesses to the integrated data. The horizontal views can provide effective accesses to complex queries of OLAP or e-business. However, we have a problem of occurring maintenance of the horizontal views since data sources are distributed over remote sites. We need a method that propagates the changes of source tables to the corresponding horizontal views. In this paper, we address incremental maintenance of horizontal views that makes it possible to reflect the changes of source tables efficiently. We first propose an overall framework that processes queries over horizontal views transformed from source tables in a vertical form. Under the proposed framework, we propagate the change of vertical tables to the corresponding horizontal views. In order to execute this view maintenance process efficiently, we keep every change of vertical tables in a differential file and then modify the horizontal views with the differential file. Because the differential file is represented as a vertical form, its tuples should be converted to those in a horizontal form to apply them to the out-of-date horizontal view. With this mechanism, horizontal views can be efficiently refreshed with the changes in a differential file without accessing source tables. Experimental results show that the proposed method improves average performance by 1.2$\sim$5.0 times over the existing methods.