Incremental topological spatial association rule mining and clustering from geographical datasets using probabilistic approach-Reference-Cited by-同舟云学术

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Incremental topological spatial association rule mining and clustering from geographical datasets using probabilistic approach

Published:2018-10 Issue:4 Volume:30 Page:510-523
ISSN:1319-1578
Container-title:Journal of King Saud University - Computer and Information Sciences
language:en
Short-container-title:Journal of King Saud University - Computer and Information Sciences

Author:

Jayababu Y.,Varma G.P.S.,Govardhan A.

Publisher

Elsevier BV

Subject

General Computer Science

Reference29 articles.

1. Fast algorithms for mining association rules;Agrawal,1994

2. Mining association rules between sets of items in large databases;Agrawal,1993

3. Probabilistic D-clustering;Ben-Israel;J. Classif.,2008

4. Mining multiple-level spatial association rules for objects with a broad boundary;Clementini;Data Knowl. Eng.,2000

5. A comprehensive framework for spatial association rule mining;Dao,2012

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2. Knowledge Discovery Web Service for Spatial Data Infrastructures;ISPRS International Journal of Geo-Information;2020-12-31

3. A dynamic classification unit for online segmentation of big data via small data buffers;Decision Support Systems;2020-01

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