STING – Statistical Information Grid in Data Mining

STING is a Grid-Based Clustering Technique. In STING, the dataset is recursively divided in a hierarchical manner. After the dataset, each cell is divided into a different number of cells. And after the cell, the statistical measures of the cell are collected, which helps answer the query as quickly as possible.

Grid-Based Method in Data Mining:

In Grid-Based Methods, the space of instance is divided into a grid structure. Clustering techniques are then applied using the Cells of the grid, instead of individual data points, as the base units. The biggest advantage of this method is to improve the processing time.

Statistical Information Grid(STING):

A STING is a grid-based clustering technique. It uses a multidimensional grid data structure that quantifies space into a finite number of cells. Instead of focusing on data points, it focuses on the value space surrounding the data points.

In STING, the spatial area is divided into rectangular cells and several levels of cells at different resolution levels. High-level cells are divided into several low-level cells.

In STING Statistical Information about attributes in each cell, such as mean, maximum, and minimum values, are precomputed and stored as statistical parameters. These statistical parameters are useful for query processing and other data analysis tasks.

The statistical parameter of higher-level cells can easily be computed from the parameters of the lower-level cells.

How STING  Work:

Step 1: Determine a layer, to begin with.

Step 2: For each cell of this layer, it calculates the confidence interval or estimated range of probability that this is cell is relevant to the query.

Step 3: From the interval calculate above, it labels the cell as relevant or not relevant.

Step 4: If this layer is the bottom layer, go to point 6, otherwise, go to point 5.

Step 5: It goes down the hierarchy structure by one level. Go to point 2 for those cells that form the relevant cell of the high-level layer.

Step 6: If the specification of the query is met, go to point 8, otherwise go to point 7.

Step 7: Retrieve those data that fall into the relevant cells and do further processing. Return the result that meets the requirement of the query. Go to point 9.

Step 8: Find the regions of relevant cells. Return those regions that meet the requirement of the query. Go to point 9.

Step 9: Stop or terminate.

Advantages:

• Grid-based computing is query-independent because the statistics stored in each cell represent a summary of the data in the grid cells and are query-independent. 
• The grid structure facilitates parallel processing and incremental updates. 

Disadvantage:

• The main disadvantage of Sting (Statistics Grid). As we know, all cluster boundaries are either horizontal or vertical, so no diagonal boundaries are detected.