Databases Reference
In-Depth Information
7.6
Pattern Exploration and Application
For discovered frequent patterns, is there any way the mining process can return addi-
tional information that will help us to better understand the patterns? What kinds of
applications exist for frequent pattern mining? These topics are discussed in this section.
Section 7.6.1 looks at the automated generation of
semantic annotations
for frequent
patterns. These are dictionary-like annotations. They provide semantic information
relating to patterns, based on the context and usage of the patterns, which aids in their
understanding. Semantically similar patterns also form part of the annotation, provid-
ing a more direct connection between discovered patterns and any other patterns already
known to the users.
Section 7.6.2 presents an overview of applications of frequent pattern mining. While
the applications discussed in Chapter 6 and this chapter mainly involve market basket
analysis and correlation analysis, there are many other areas in which frequent pattern
mining is useful. These range from data preprocessing and classification to clustering
and the analysis of complex data.
7.6.1
Semantic Annotation of Frequent Patterns
Pattern mining typically generates a huge set of frequent patterns without providing
enough information to interpret the meaning of the patterns. In the previous section,
we introduced pattern processing techniques to shrink the size of the output set of fre-
quent patterns such as by extracting redundancy-aware top-
k
patterns or compressing
the pattern set. These, however, do not provide any semantic interpretation of the pat-
terns. It would be helpful if we could also generate semantic annotations for the frequent
patterns found, which would help us to better understand the patterns.
“
What is an appropriate semantic annotation for a frequent pattern?
” Think about
what we find when we look up the meaning of terms in a dictionary. Suppose we are
looking up the term
pattern
. A dictionary typically contains the following components
to explain the term:
1.
A set of definitions
, such as “a decorative design, as for wallpaper, china, or textile
fabrics, etc.; a natural or chance configuration”
2.
Example sentences
, such as “
patterns
of frost on the window; the behavior
patterns
of
teenagers, . . . ”
3.
Synonyms from a thesaurus
, such as “model, archetype, design, exemplar, motif, . . . .”
Analogically, what if we could extract similar types of semantic information and pro-
vide such structured annotations for frequent patterns? This would greatly help users
in interpreting the meaning of patterns and in deciding on how or whether to further
explore them. Unfortunately, it is infeasible to provide such precise semantic defini-
tions for patterns without expertise in the domain. Nevertheless, we can explore how to
approximate
such a process for frequent pattern mining.
