Abstract:
With the sheer amount of data stored, presented and
exchanged using XML nowadays, the ability to extract knowledge from
XML data sources becomes increasingly important and desirable. This
paper aims to integrate the newly emerging XML technology with data
mining technology, using association rule mining as a case in point.
Compared with traditional association mining in the well-structured
world (e.g., relational databases), mining from XML data is faced
with more challenges due to the inherent flexibilities of XML in both
structure and semantics. The primary challenges include 1) a more
complicated hierarchical data structure; 2) an ordered data context; and
3) a much bigger data size. To tackle these challenges, in this paper, we
propose an extended XML-enabled association rule framework, which
is flexible and powerful enough to represent both simple and complex
structured association relationships inherent in XML data.
