STatistical Information Grid (STING) is a grid-based clustering algorithm. The dataset is recursively divided into a hierarchy structure. The whole input dataset serves as the root node in the hierarchy structure. Each cell/unit in a layer is composed of a couple of cells/units in the lower layer. An example is shown in the following diagram:
To support the query for a dataset, the statistical information of each unit is calculated in advance for further processing; this information is also called statistics parameters.
The characteristics of STING algorithms are (but not limited to) the following:
Please take a look at the R codes file ch_06_sting.R
from the bundle of R codes for the previously mentioned algorithm. The codes can be tested with the following command:
> source("ch_06_sting.R")
Depending on statistical, data-mining, and knowledge-discovery techniques, recommendation systems are being used by most of the e-commerce sites to make it easy for consumers to find products to purchase. Three main parts: representation of input data, neighborhood formation, and recommendation generation are shown in the following diagram:
3.144.87.206