Abstract
This paper addresses the problem of timestamped event sequence matching, a new type of sequence matching that retrieves the occurrences of interesting patterns from a timestamped event sequence. Timestamped event sequence matching is useful for discovering temporal causal relationships among timestamped events. In this paper, we first point out the shortcomings of prior approaches to this problem and then propose a novel method that employs an R ∗ -tree to overcome them. To build an R ∗ -tree, it places a time window at every position of a timestamped event sequence and represents each window as an n-dimensional rectangle by considering the first and last occurrence times of each event type. Here, n is the total number of disparate event types that may occur in a target application. When n is large, we apply a grouping technique to reduce the dimensionality of an R ∗ -tree. To retrieve the occurrences of a query pattern from a timestamped event sequence, the proposed method first identifies a small number of candidates by searching an R ∗ -tree and then picks out true answers from them. We prove its robustness formally, and also show its effectiveness via extensive experiments.
This work was partially supported by Korea Research Foundation Grant funded by Korea Government (MOEHRD, Basic Research Promotion Fund) (KRF-2005-206-D00015), by the ITRC support program(MSRC) of IITA, and by the research fund of Korea Research Foundation with Grant KRF-2003-041-D00486.
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References
Agrawal, R., Faloutsos, C., Swami, A.: Efficient Similarity Searchin Sequence Databases. In: Lomet, D.B. (ed.) FODO 1993. LNCS, vol. 730, pp. 69–84. Springer, Heidelberg (1993)
Agrawal, R., Lin, K., Sawhney, H.S., Shim, K.: Fast Similarity Search in the Presence of Noise, Scaling, and Translation in Time-Series Databases. In: Proc. Int’l. Conf. on Very Large Data Bases, VLDB, September 1995, pp. 490–501 (1995)
Beckmann, N., Kriegel, H., Schneider, R., Seeger, B.: The R*-tree: An Efficient and Robust Access Method for Points and Rectangles. In: Proc. Int’l. Conf. on Management of Data, ACM SIGMOD, pp. 322–331 (1990)
Chu, K.K.W., Wong, M.H.: Fast Time-Series Searching with Scaling and Shifting. In: Proc. Int’l. Symp. on Principles of Database Systems, ACM PODS, May 1999, pp. 237–248 (1999)
Faloutsos, C., Ranganathan, M., Manolopoulos, Y.: Fast Subsequence Matching in Time-series Databases. In: Proc. Int’l. Conf. on Management of Data, ACM SIGMOD, May 1994, pp. 419–429 (1994)
Goldin, D.Q., Kanellakis, P.C.: On Similarity Queries for Time-Series Data: Constraint Specification and Implementation. In: Montanari, U., Rossi, F. (eds.) CP 1995. LNCS, vol. 976, pp. 137–153. Springer, Heidelberg (1995)
Kim, S.W., Park, S.H., Chu, W.W.: An Index-Based Approach for Similarity Search Supporting Time Warping in Large Sequence Databases. In: Proc. Int’l. Conf. on Data Engineering, IEEE ICDE, pp. 607–614 (2001)
Moon, Y.S., Whang, K.Y., Loh, W.K.: Duality-Based Subsequence Matching in Time-Series Databases. In: Proc. Int’l. Conf. on Data Engineering, IEEE ICDE, pp. 263–272 (2001)
Park, S., Chu, W.W., Yoon, J., Hsu, C.: Efficient Searches for Similar Subsequences of Different Lengths in Sequence Databases. In: Proc. Int’l. Conf. on Data Engineering, IEEE ICDE, pp. 23–32 (2000)
Park, S., Won, J., Yoon, J., Kim, S.: An Index-Based Method for Timestamped Event Sequence Matching. Technical Report, Yonsei University (2004)
Rafiei, D., Mendelzon, A.: Similarity-Based Queries for Time-Series Data. In: Proc. Int’l. Conf. on Management of Data, ACM SIGMOD, pp. 13–24 (1997)
Rafiei, D.: On Similarity-Based Queries for Time Series Data. In: Proc. Int’l. Conf. on Data Engineering, IEEE ICDE, pp. 410–417 (1999)
Stephen, G.A.: String Searching Algorithms. World Scientific Publishing, Singapore (1994)
Wang, H., Perng, C., Fan, W., Park, S., Yu, P.: Indexing Weighted Sequences in Large Databases. In: Proc. Int’l. Conf. on Data Engineering, IEEE ICDE, pp. 63–74 (2003)
Weber, R., Schek, H.-J., Blott, S.: A Quantitative Analysis and Performance Study for Similarity Search Methods in High-Dimensional Spaces. In: Proc. Int’l. Conf. on Very Large Data Bases, VLDB, pp. 194–205 (1998)
Yi, B.K., Faloutsos, C.: Fast Time Sequence Indexing for Arbitrary Lp Norms. In: Proc. Int’l. Conf. on Very Large Data Bases, VLDB, pp. 385–394 (2000)
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Park, S., Won, JI., Yoon, JH., Kim, SW. (2005). An Index-Based Method for Timestamped Event Sequence Matching. In: Andersen, K.V., Debenham, J., Wagner, R. (eds) Database and Expert Systems Applications. DEXA 2005. Lecture Notes in Computer Science, vol 3588. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11546924_48
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DOI: https://doi.org/10.1007/11546924_48
Publisher Name: Springer, Berlin, Heidelberg
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