论文信息 - CLUSTERING AND NOISE DETECTION FOR GEOGRAPHIC KNOWLEDGE DISCOVERY

CLUSTERING AND NOISE DETECTION FOR GEOGRAPHIC KNOWLEDGE DISCOVERY

Ample amount of geographic data has been collected with modern data acquisition techniques such as a Global Positioning System, high resolution remote sensing and internet based volunteered geographic information. Spatial datasets are large in size, multidimensional and have high complexity measures. To address these challenges Spatial Data Mining (SDM) for Geographic Knowledge Discovery (GKD) are the emerging fields for extraction of useful information and knowledge mining for many applications. This paper addresses the clustering and noise detection technique for spatial data. We considered multidimensional spatial data to provide feasible environment to place sensitive devices in a laboratory by using the data collected from the sensors. Various sensors were used to collect the spatial and temporal data. The GDBSCAN algorithm is used for clustering, which relies on density based notation of clustering and is designed to discover clusters of arbitrary shape and distinguish noise. The proposed work reduces the computation cost and increase the performance.

Mohan J. Kumar | S. Kotha | V. Ramulu | N. Kumar | K. S. Reddy

[1] Hans-Peter Kriegel,et al. Density-Based Clustering in Spatial Databases: The Algorithm GDBSCAN and Its Applications , 1998, Data Mining and Knowledge Discovery.

[2] Mohammed Otair,et al. Approximate k-nearest neighbour based spatial clustering using k-d tree , 2013, ArXiv.

[3] Vipin Kumar,et al. Finding Clusters of Different Sizes, Shapes, and Densities in Noisy, High Dimensional Data , 2003, SDM.

[4] Jiawei Han,et al. Efficient and Effective Clustering Methods for Spatial Data Mining , 1994, VLDB.

[5] Hans-Peter Kriegel,et al. A Density-Based Algorithm for Discovering Clusters in Large Spatial Databases with Noise , 1996, KDD.

[6] Richa Sharma,et al. Local Density Differ Spatial Clustering in , 2013 .

[7] Sang-Wook Kim,et al. SD-Miner: A spatial data mining system , 2009, 2009 IEEE International Conference on Network Infrastructure and Digital Content.

[8] Padhraic Smyth,et al. Knowledge Discovery and Data Mining: Towards a Unifying Framework , 1996, KDD.

[9] Mehmet Sayal,et al. A Distributed Clustering Algorithm for Web-Based Access Patterns , 2000 .

[10] Suresh Kotha,et al. Spatial Data Mining using Cluster Analysis , 2012 .

[11] Anil K. Jain,et al. Algorithms for Clustering Data , 1988 .

[12] Hans-Peter Kriegel,et al. A Database Interface for Clustering in Large Spatial Databases , 1995, KDD.

[13] Lovely Sharma,et al. A Review on Density based Clustering Algorithms for Very Large Datasets , 2013 .