Q. Ding, Q. Ding, and W. Perrizo, "Association Rule Mining on Remotely Sensed Images Using P-trees," Pacific-Asian Conference on Knowledge Discovery and Data Mining, PAKDD-2002. Home/Search Document Details and Download
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Mining Image Datasets Using Perceptual Association Rules - Tesic, Newsam, Manjunath (Correct)
....X and confidence Y . It is not clear, however, that the results from applying the technique to a dataset of synthetic images composed of basic colored shapes would generalize to real images for which segmentation and notions of region similarity present a significant challenge. Ding et al. [4] extract association rules from remote sensed imagery by considering set ranges of the spectral bands to be items and the pixels to be transactions. They also consider auxiliary information at each pixel location, such as crop yield, to derive association rules of the form Band 1 in the range [a, ....
Qin Ding, Qiang Ding, and William Perrizo, "Association rule mining on remotely sensed images using p-trees," in Proc. PAKDD, 2002.
Efficient Hierarchical Clustering of Large Data . . . - Denton, al. Self-citation (Ding Perrizo) (Correct)
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Qin Ding, Qiang Ding, William Perrizo, "Association Rule Mining on remotely sensed images using P-trees", PAKDD-2002.
Association Rule Mining on Remotely Sensed Imagery Using P-Trees - Ding (2002) (3 citations) Self-citation (Ding Perrizo) (Correct)
....representations of each bSQ file. Fast P tree operations, especially the fast AND operation, provide possibilities for efficient data mining. We have proposed P tree based efficient data mining algorithms, such as association rule mining [DDP02b] decision tree induction [DDP02a], and k nearest neighbor classification [KDP02] In this dissertation, we will focus on P tree based association rule mining of RSI data. The basic idea of our approach is that, by using P trees during the mining process, database scans can be replaced by appropriate P tree operations, which are ....
....archeology, mineral exploration, Genomics Proteomics, VLSI design, and environmental analysis and control. Besides association rule mining, we can also perform other data mining applications, such as classification and clustering. We proposed a decision tree induction algorithm based on P trees [DDP02a] and a k nearest neighbor classification algorithm using P trees [KDP02] We believe that there are open areas in data mining which will benefit from using P trees, such as sequential pattern mining and data mining on data streams. 121 ....
Q. Ding, Q. Ding, and W. Perrizo, "Association Rule Mining on Remotely Sensed Images Using P-trees," Proceedings of the PAKDD, Taipei, Taiwan, May 2002, pp. 66-79.
Efficient Hierarchical Clustering of Large Data Sets.. - Denton, Ding, Perrizo.. Self-citation (Ding Perrizo) (Correct)
....algorithm that uses k medoids related ideas without incurring the high time complexity. In Birch, data are broken up into local clustering features and then combined into CF Trees. In contrast to Birch we determine cluster centers that are defined globally. We represent data in the form of P trees [10, 11, 12, 13, 14], which are efficient both in the storage requirements and the time complexity of computing global counts. The rest of the paper is organized as follows. In section 2 we analyze the reasons for high time complexity of k medoids based algorithms and show how this complexity can be avoided using a ....
....requires us to have a fast method of finding data points based on their feature attribute values. Density based algorithms such as DENCLUE achieve this goal by saving data in a special data structure that allows referring to neighbors. We use a data structure, namely a Peano Count Tree (or P tree) [10, 11, 12, 13, 14] that allows fast calculation of counts of data points based on their attribute values. 4.1 A Summary of P Tree Features Many types of data show continuity in dimensions that are not themselves used as data mining attributes. Spatial data that is mined independently of location will consist of ....
Qin Ding, Qiang Ding, William Perrizo, "Association Rule Mining on Remotely Sensed Images using P-trees", PAKDD-2002.
Chapter 2. Data Mining Using P-Tree - Relational Systems Data (Correct)
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Q. Ding, Q. Ding, and W. Perrizo, "Association Rule Mining on Remotely Sensed Images Using P-trees," Pacific-Asian Conference on Knowledge Discovery and Data Mining, PAKDD-2002.
Chapter 7. Paper 3: - Efficient Hierarchical Clustering (Correct)
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Q. Ding, Q. Ding, and W. Perrizo, "Association Rule Mining on Remotely Sensed Images Using P-trees," Pacific Asian Conference on Knowledge Discovery and Data Mining (PAKDD-2002.
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