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An Incrementally Trainable Statistical Approach to Information Extraction. Edition No. 1
VDM Publishing House, July 2008, Pages: 216
Most of the information stored in digital form is hidden in natural
language texts. The purpose of Information Extraction (IE) is to find
desired pieces of information in unstructured or weakly structured texts
and store them in a form that is suitable for automatic querying and
processing.
This book presents a innovative approach to statistical information
extraction. It introduces a new algorithm which supports functionality not
available in previous IE systems, such as interactive incremental training
to reduce the human training effort. The system also utilizes new sources
of information, employing rich tree-based context representations to
combine document structure (HTML or XML markup) with linguistic and
semantic information.
The resulting IE system is designed as a generic framework for statistical
information extraction. All core components can be modified or exchanged
independently of each other.
This book is of interest for professionals who have to deal with large
amounts of weakly structured information and seek ways to automate this
process, as well as for researchers and practitioners active in the fields
of text mining and text classification.
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