Text Mining with MATLAB provides a comprehensive introduction to text mining using MATLAB. It's
designed to help text mining practitioners as well as those with little-to-no experience with
text mining in general familiarize themselves with MATLAB and its complex applications. The
first part provides an introduction to basic procedures for handling and operating with text
strings. Then it reviews major mathematical modeling approaches. Statistical and geometrical
models are also described along with main dimensionality reduction methods. Finally it
presents some specific applications such as document clustering classification search and
terminology extraction.All descriptions presented are supported with practical examples that
are fully reproducible. Further reading as well as additional exercises and projects are
proposed at the end of each chapter for those readers interested in conducting further
experimentation. The first part provides an introduction to basic procedures for handling and
operating with text strings. Then it reviews major mathematical modeling approaches.
Statistical and geometrical models are also described along with main dimensionality reduction
methods. Finally it presents some specific applications such as document clustering
classification search and terminology extraction. The first part provides an introduction to
basic procedures for handling and operating with text strings. Then it reviews major
mathematical modeling approaches. Statistical and geometrical models are also described along
with main dimensionality reduction methods. Finally it presents some specific applications
such as document clustering classification search and terminology extraction.All descriptions
presented are supported with practical examples that are fully reproducible. Further reading
as well as additional exercises and projects are proposed at the end of each chapter for those
readers interested in conducting further experimentation. The first part provides an
introduction to basic procedures for handling and operating with text strings. Then it reviews
major mathematical modeling approaches. Statistical and geometrical models are also described
along with main dimensionality reduction methods. Finally it presents some specific
applications such as document clustering classification search and terminology extraction.
All descriptions presented are supported with practical examples that are fully reproducible.
Further reading as well as additional exercises and projects are proposed at the end of each
chapter for those readers interested in conducting further experimentation. All descriptions
presented are supported with practical examples that are fully reproducible. Further reading
as well as additional exercises and projects are proposed at the end of each chapter for those
readers interested in conducting further experimentation.
