O'Reilly logo

Mobile Intelligence by Bala Srinivasan, Ling Tan, Jianhua Ma, Agustinus Borgy Waluyo, Laurence T. Yang

Stay ahead with the world's most comprehensive technology and business learning platform.

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, tutorials, and more.

Start Free Trial

No credit card required

11.4 FINDING OTHER INTERESTING PATTERNS

The former section focused on the extension of sequential pattern mining. This section introduces other mining approaches to find interesting patterns from moving object databases.

11.4.1 Spatio-temporal Association Rules

Association rule mining is one of the most popular topics in data mining [1, 25, 56]. An example of an association rule is {notebook} ⇒ {pen}. The rule indicates that if a notebook is purchased, it is likely that a pen is also purchased. So far, various association rule mining methods for large transaction data have been proposed.

Verhein and Chawla [61] extend the notion of association rules to the spatio-temporal context. They call such rules spatio-temporal association rules. The most simple type of rule can be written as

images

where ri, rj are spatial regions and Δi, Δj are time intervals that satisfy Δi < Δj. The above rule says that objects appearing in ri during time interval Δi will appear in region rj during Δj. To find interesting rules, they propose the notion of spatial support:

images

where σ((ri, Δi) ⇒ (rj, Δj)) denotes the conventional support of the rule—the number of objects that satisfy the rule and area(r) is the area of region r. The smaller the area covered, the higher the spatial support of the rule.

In addition, ...

With Safari, you learn the way you learn best. Get unlimited access to videos, live online training, learning paths, books, interactive tutorials, and more.

Start Free Trial

No credit card required