Unsupervised Information Extraction by Text Segmentation

• Main Authors: Cortez, Eli. (Author), Silva, Altigran S. (Author)
• Corporate Author: SpringerLink (Online service)
• Format: Electronic
• Language: English
• Published: Cham : Springer International Publishing : Imprint: Springer, 2013.
• Series: SpringerBriefs in Computer Science,
• Subjects: Computer science.; Database management.; Data mining.; Information storage and retrieval systems.; Computer Science.; Database Management.; Data Mining and Knowledge Discovery.; Information Storage and Retrieval.
• Online Access: https://ezaccess.library.uitm.edu.my/login?url=http://dx.doi.org/10.1007/978-3-319-02597-1

A new unsupervised approach to the problem of Information Extraction by Text Segmentation (IETS) is proposed, implemented and evaluated herein. The authors approach relies on information available on pre-existing data to learn how to associate segments in the input string with attributes of a given...

Table of Contents:

• Foreword
• Preface
• Introduction
• Related Work
• Exploiting Pre-Existing Datasets to Support IETS
• ONDUX
• JUDIE
• iForm
• Conclusions and Future Work.