Towards Efficient Discovery of Spatially Interesting Patterns in Geo-referenced Sequential Databases-Reference-Cited by-同舟云学术

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Towards Efficient Discovery of Spatially Interesting Patterns in Geo-referenced Sequential Databases

Published:2023-07-10 Issue: Volume: Page:
ISSN:
Container-title:35th International Conference on Scientific and Statistical Database Management
language:
Short-container-title:

Author:

Suzuki Shota¹^ORCID,Rage Uday Kiran¹^ORCID

Affiliation:

1. The University of Aizu, Japan

Funder

Japan Society for the Promotion of Science

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3603719.3603743

Reference19 articles.

1. [n. d.]. Atmospheric Environmental Regional Observation System : AEROS. http://soramame.taiki.go.jp/. [n. d.]. Atmospheric Environmental Regional Observation System : AEROS. http://soramame.taiki.go.jp/.

2. [n. d.]. Code and Data. https://github.com/udayRage/codeData. [n. d.]. Code and Data. https://github.com/udayRage/codeData.

3. Rakesh Agrawal , Tomasz Imieliński , and Arun Swami . 1993 . Mining Association Rules Between Sets of Items in Large Databases. In International Conference on Management of Data. 207–216 . Rakesh Agrawal, Tomasz Imieliński, and Arun Swami. 1993. Mining Association Rules Between Sets of Items in Large Databases. In International Conference on Management of Data. 207–216.

4. R. Agrawal and R. Srikant. 1995. Mining sequential patterns. In ICDE. 3-14. https://doi.org/10.1109/ICDE.1995.380415 10.1109/ICDE.1995.380415

5. R. Agrawal and R. Srikant. 1995. Mining sequential patterns. In ICDE. 3-14. https://doi.org/10.1109/ICDE.1995.380415

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