Adaptive Two-Phase Spatial Association Rules Mining Method
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| Format: | Artículo científico |
| Sprache: | en |
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Universidad Nacional de La Plata
2006
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| _version_ | 1876436444967337984 |
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| author | Chin-Feng Lee |
| author_facet | Chin-Feng Lee |
| contents | Adaptive Two-Phase Spatial Association Rules Mining Method Chin-Feng Lee Mei-Hsiu Chen Computación Data Mining Spatial Database Remote Sensed Image Spatial Association Rules Since huge amounts of spatial data can be easily collected from various applications, ranging from remote sensing technology to geographical information system, the extraction and comprehension of spatial knowledge is a more and more important task. Many excellent studies on Remote Sensed Image (RSI) have been conducted for potential relationships of crop yield. However, most of them suffer from the performance problem because their techniques for mining association rules are based on Apriori algorithm. In this paper, two efficient algorithms, two-phase spatial association rules mining and adaptive two-phase spatial association rules mining, are proposed for address the above problem. Both methods primarily conduct two phase algorithms by creating Histogram Generators for fast generating coarse-grained spatial association rules, and further mining the fine-grained spatial association rules w.r.t the coarse-grained frequently patterns obtained in the first phase. Adaptive two-phase spatial association rules mining method conducts the idea of partition on an image for efficiently quantizing out non-frequent patterns and thus facilitate the following two phase process. Such two-phase approaches save much computations and will be shown by lots of experimental results in the paper. 2006 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067342001 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.01 Vol.6 |
| format | Artículo científico |
| id | redalyc_638067342001 |
| institution | Redalyc |
| language | en |
| publishDate | 2006 |
| publisher | Universidad Nacional de La Plata |
| spellingShingle | Adaptive Two-Phase Spatial Association Rules Mining Method Chin-Feng Lee Computación Data Mining Spatial Database Remote Sensed Image Spatial Association Rules Adaptive Two-Phase Spatial Association Rules Mining Method Chin-Feng Lee Mei-Hsiu Chen Computación Data Mining Spatial Database Remote Sensed Image Spatial Association Rules Since huge amounts of spatial data can be easily collected from various applications, ranging from remote sensing technology to geographical information system, the extraction and comprehension of spatial knowledge is a more and more important task. Many excellent studies on Remote Sensed Image (RSI) have been conducted for potential relationships of crop yield. However, most of them suffer from the performance problem because their techniques for mining association rules are based on Apriori algorithm. In this paper, two efficient algorithms, two-phase spatial association rules mining and adaptive two-phase spatial association rules mining, are proposed for address the above problem. Both methods primarily conduct two phase algorithms by creating Histogram Generators for fast generating coarse-grained spatial association rules, and further mining the fine-grained spatial association rules w.r.t the coarse-grained frequently patterns obtained in the first phase. Adaptive two-phase spatial association rules mining method conducts the idea of partition on an image for efficiently quantizing out non-frequent patterns and thus facilitate the following two phase process. Such two-phase approaches save much computations and will be shown by lots of experimental results in the paper. 2006 artículo científico 1666-6046 https://www.redalyc.org/articulo.oa?id=638067342001 en http://www.redalyc.org/revista.oa?id=6380 Journal of Computer Science and Technology application/pdf Universidad Nacional de La Plata Journal of Computer Science and Technology (Argentina) Num.01 Vol.6 |
| title | Adaptive Two-Phase Spatial Association Rules Mining Method |
| topic | Computación Data Mining Spatial Database Remote Sensed Image Spatial Association Rules |
| url | https://www.redalyc.org/articulo.oa?id=638067342001 |