Spatial Analysis

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Spatial Analysis
2011-06-11 11:08:12

SA 10
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  1. What is Clustering?
    • Clustering algorithms divides a dataset into natural groups. Instances in the same cluster are similar to each other, they share certain properties.
    • Cluster analysis is used to reduce data (dimension) to a number of multivariate classes.
  2. Name and explain approaches of clustering.
    • Partitioning: divide the data into a given number of clusters. (it uses k-means)
    • Hierarchical: create a tree based on the similiraties/ distance of items.
    • Density-based: find continguous areas with high density.
    • Grid-based: divide the data space into grid cells.
  3. what is the pupose of Clustering by Partitioning?
    We try to make properties as similar as possible within groups and as different as possible between groups.
  4. What are Partitioning Methods?
    • K-medoids: use the centermost cluster member instead of the mean.
    • EM: define the cluster by a probability distribution instead of a centroid.
    • Guaranteed to find a local optimum.
    • Not globally optimal clustering.
    • Tend to find circular clusters.
  5. What is the disadvantage of Hierarchical Clustering?
    You have to use your common sense and your skill to do the clustering.
  6. Diagram of Hierarchical Clustering.
  7. What is Density-based clustering good for?
    • For finding non-spherical clusters.
    • Clusters do not necessarily cover all points.
  8. Explain Grid-based clustering.
    • Goal: find areas with high point desity.
    • divide the space to grid cells.
    • compute the density of points in each cell.
    • use the high-density cells to define clusters.
    • more effective than density-based clustering.
  9. Spatio-temporal movement at a macro sacle?
    • Time is continuous.
  10. Spatio-temporal movement at a micro sacle?
  11. What is Tourism Market Segmentation?
    A process of dividing a market into homogeneous subgroups. Tourists in the same group are similar to each other, and different from other groups.
  12. What are the objectives of market segmentation?
    • Identifying and characterising groups of tourists.
    • Focusing advertising efforts for greater impacts.
    • Identifying likely targerts for new tourist products.
    • Improving existing products or services.
    • Looking for new product services.
    • Assessing the impact of a competitor's new offering.
    • Establishing a better tourst attraction image.
  13. What are the advantages of EM clustering algorithm?
    • Primarily catergorical variables.
    • Computing the number of clusters.
    • Tending to be a samll number of significant clusters and a number of othes that are not interesting.
    • Each tourist is assigned into a certain cluster with certain probability, which govern the set of attribute values of observations in the cluster.