Paper Title
Words Sequence Pattern Mining Using Pattern Taxonomy Model
Abstract
The text data of text mining has gradually become a new follow a line of investigation. Text
clustering can greatly simplify browsing large collections of documents by reorganizing t hem into a
smaller number of patterns in text documents manageable clusters. Text clustering is mainly used for a
document clustering system which clusters the set of documents based on the user typed key term.
Firstly the system preprocesses the set of documents and the user given terms. We use the feature evaluation to
reduce the dimensionality of high -dimensional text vector. The system then identifies the term frequency
and then those frequencies are weighted by using the inverted document frequency method. Then this
weight of documents is used for clustering. Feature clustering is a powerful method to reduce the dimensionality
of feature vectors for text classification.