• Title/Summary/Keyword: Lower-Dimensional Transformations

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Hybrid Lower-Dimensional Transformation for Similar Sequence Matching (유사 시퀀스 매칭을 위한 하이브리드 저차원 변환)

  • Moon, Yang-Sae;Kim, Jin-Ho
    • The KIPS Transactions:PartD
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    • v.15D no.1
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    • pp.31-40
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    • 2008
  • We generally use lower-dimensional transformations to convert high-dimensional sequences into low-dimensional points in similar sequence matching. These traditional transformations, however, show different characteristics in indexing performance by the type of time-series data. It means that the selection of lower-dimensional transformations makes a significant influence on the indexing performance in similar sequence matching. To solve this problem, in this paper we propose a hybrid approach that integrates multiple transformations and uses them in a single multidimensional index. We first propose a new notion of hybrid lower-dimensional transformation that exploits different lower-dimensional transformations for a sequence. We next define the hybrid distance to compute the distance between the transformed sequences. We then formally prove that the hybrid approach performs the similar sequence matching correctly. We also present the index building and the similar sequence matching algorithms that use the hybrid approach. Experimental results for various time-series data sets show that our hybrid approach outperforms the single transformation-based approach. These results indicate that the hybrid approach can be widely used for various time-series data with different characteristics.

NBR-Safe Transform: Lower-Dimensional Transformation of High-Dimensional MBRs in Similar Sequence Matching (MBR-Safe 변환 : 유사 시퀀스 매칭에서 고차원 MBR의 저차원 변환)

  • Moon, Yang-Sae
    • Journal of KIISE:Databases
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    • v.33 no.7
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    • pp.693-707
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    • 2006
  • To improve performance using a multidimensional index in similar sequence matching, we transform a high-dimensional sequence to a low-dimensional sequence, and then construct a low-dimensional MBR that contains multiple transformed sequences. In this paper we propose a formal method that transforms a high-dimensional MBR itself to a low-dimensional MBR, and show that this method significantly reduces the number of lower-dimensional transformations. To achieve this goal, we first formally define the new notion of MBR-safe. We say that a transform is MBR-safe if a low-dimensional MBR to which a high-dimensional MBR is transformed by the transform contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. We then propose two MBR-safe transforms based on DFT and DCT, the most representative lower-dimensional transformations. For this, we prove the traditional DFT and DCT are not MBR-safe, and define new transforms, called mbrDFT and mbrDCT, by extending DFT and DCT, respectively. We also formally prove these mbrDFT and mbrDCT are MBR-safe. Moreover, we show that mbrDFT(or mbrDCT) is optimal among the DFT-based(or DCT-based) MBR-safe transforms that directly convert a high-dimensional MBR itself into a low-dimensional MBR. Analytical and experimental results show that the proposed mbrDFT and mbrDCT reduce the number of lower-dimensional transformations drastically, and improve performance significantly compared with the $na\"{\i}ve$ transforms. These results indicate that our MBR- safe transforms provides a useful framework for a variety of applications that require the lower-dimensional transformation of high-dimensional MBRs.

Spatial Locality Preservation Metric for Constructing Histogram Sequences (히스토그램 시퀀스 구성을 위한 공간 지역성 보존 척도)

  • Lee, Jeonggon;Kim, Bum-Soo;Moon, Yang-Sae;Choi, Mi-Jung
    • Journal of Information Technology and Architecture
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    • v.10 no.1
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    • pp.79-91
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    • 2013
  • This paper proposes a systematic methodology that could be used to decide which one shows the best performance among space filling curves (SFCs) in applying lower-dimensional transformations to histogram sequences. A histogram sequence represents a time-series converted from an image by the given SFC. Due to the high-dimensionality nature, histogram sequences are very difficult to be stored and searched in their original form. To solve this problem, we generally use lower-dimensional transformations, which produce lower bounds among high dimensional sequences, but the tightness of those lower-bounds is highly affected by the types of SFC. In this paper, we attack a challenging problem of evaluating which SFC shows the better performance when we apply the lower-dimensional transformation to histogram sequences. For this, we first present a concept of spatial locality, which comes from an intuition of "if the entries are adjacent in a histogram sequence, their corresponding cells should also be adjacent in its original image." We also propose spatial locality preservation metric (slpm in short) that quantitatively evaluates spatial locality and present its formal computation method. We then evaluate five SFCs from the perspective of slpm and verify that this evaluation result concurs with the performance evaluation of lower-dimensional transformations in real image matching. Finally, we perform k-NN (k-nearest neighbors) search based on lower-dimensional transformations and validate accuracy of the proposed slpm by providing that the Hilbert-order with the highest slpm also shows the best performance in k-NN search.

Efficient Time-Series Subsequence Matching Using MBR-Safe Property of Piecewise Aggregation Approximation (부분 집계 근사법의 MBR-안전 성질을 이용한 효율적인 시계열 서브시퀀스 매칭)

  • Moon, Yang-Sae
    • Journal of KIISE:Databases
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    • v.34 no.6
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    • pp.503-517
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    • 2007
  • In this paper we address the MBR-safe property of Piecewise Aggregation Approximation(PAA), and propose an of efficient subsequence matching method based on the MBR-safe PAA. A transformation is said to be MBR-safe if a low-dimensional MBR to which a high- dimensional MBR is transformed by the transformation contains every individual low-dimensional sequence to which a high-dimensional sequence is transformed. Using an MBR-safe transformation we can reduce the number of lower-dimensional transformations required in similar sequence matching, since it transforms a high-dimensional MBR itself to a low-dimensional MBR directly. Furthermore, PAA is known as an excellent lower-dimensional transformation single its computation is very simple, and its performance is superior to other transformations. Thus, to integrate these advantages of PAA and MBR-safeness, we first formally confirm the MBR-safe property of PAA, and then improve subsequence matching performance using the MBR-safe PAA. Contributions of the paper can be summarized as follows. First, we propose a PAA-based MBR-safe transformation, called mbrPAA, and formally prove the MBR-safeness of mbrPAA. Second, we propose an mbrPAA-based subsequence matching method, and formally prove its correctness of the proposed method. Third, we present the notion of entry reuse property, and by using the property, we propose an efficient method of constructing high-dimensional MBRs in subsequence matching. Fourth, we show the superiority of mbrPAA through extensive experiments. Experimental results show that, compared with the previous approach, our mbrPAA is 24.2 times faster in the low-dimensional MBR construction and improves subsequence matching performance by up to 65.9%.

Effect of phase transformations on buckling behavior of subducting slab and tectonic implication (상전이가 섭입 슬랩의 좌굴에 미치는 영향과 지체구조적 암시)

  • Lee, Changyeol
    • Journal of the Geological Society of Korea
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    • v.54 no.6
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    • pp.657-675
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    • 2018
  • The apparent thickening of the subducting slab in the shallow lower mantle has been attributed to slab buckling. However, the scaling laws have not been quantitatively evaluated for the buckling behavior of the subducting slab when phase transformations are considered. Thus, two-dimensional dynamic subduction experiments are formulated to evaluate the effect of phase transformations on the buckling behavior of the subducting slab. The model calculations show that the phase transformation from olivine to wadsleyite at a depth of 410 km plays an important role in the development of slab buckling; increased slab pull due to the endothermic phase transformation accelerates slab sinking in the upper mantle and the subducting slab reaches the lower mantle in a shorter time than that of the experiments without the phase transformation. However, the phase transformation from ringwoodite to perovskite plus $magnesiow{\ddot{u}}stite$ at a depth of 660 km retards slab sinking into the lower mantle and the subducting slab tends to be accumulated in the transformation (transition) zone. Buckling analyses show that the scaling laws predict the buckling amplitude and period of the subducting slab with small relative errors even if the phase transformations are considered. The universal phenomenon of the slab buckling can explain apparent slab thickening in the shallow lower mantle and transformation zone under the subduction zones such as Java-Sunda and Northeast Japan. In addition, the buckling behavior of the subducting slab may be related to the periodic compressions and extensions in the Cretaceous Gyeongsang basin.

Efficient Multi-Step k-NN Search Methods Using Multidimensional Indexes in Large Databases (대용량 데이터베이스에서 다차원 인덱스를 사용한 효율적인 다단계 k-NN 검색)

  • Lee, Sanghun;Kim, Bum-Soo;Choi, Mi-Jung;Moon, Yang-Sae
    • Journal of KIISE
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    • v.42 no.2
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    • pp.242-254
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    • 2015
  • In this paper, we address the problem of improving the performance of multi-step k-NN search using multi-dimensional indexes. Due to information loss by lower-dimensional transformations, existing multi-step k-NN search solutions produce a large tolerance (i.e., a large search range), and thus, incur a large number of candidates, which are retrieved by a range query. Those many candidates lead to overwhelming I/O and CPU overheads in the postprocessing step. To overcome this problem, we propose two efficient solutions that improve the search performance by reducing the tolerance of a range query, and accordingly, reducing the number of candidates. First, we propose a tolerance reduction-based (approximate) solution that forcibly decreases the tolerance, which is determined by a k-NN query on the index, by the average ratio of high- and low-dimensional distances. Second, we propose a coefficient control-based (exact) solution that uses c k instead of k in a k-NN query to obtain a tigher tolerance and performs a range query using this tigher tolerance. Experimental results show that the proposed solutions significantly reduce the number of candidates, and accordingly, improve the search performance in comparison with the existing multi-step k-NN solution.