Learning Structure and Schemas from Documents

• Corporate Author: SpringerLink (Online service)
• Other Authors: Biba, Marenglen (Editor), Xhafa, Fatos (Editor)
• Format: Electronic eBook
• Language: English
• Published: Berlin, Heidelberg : Springer Berlin Heidelberg, 2011.
• Series: Studies in Computational Intelligence, 375
• Subjects: Engineering.; Artificial intelligence.; Computational intelligence.; Computational Intelligence.; Artificial Intelligence (incl. Robotics).

The rapidly growing volume of available digital documents of various formats and the possibility to access these through Internet-based technologies, have led to the necessity to develop solid methods to properly organize and structure documents in large digital libraries and repositories. Due to th...

Table of Contents:

• From the content: Learning Structure and Schemas from Heterogeneous Domains in Networked Systems Surveyed
• Handling Hierarchically Structured Resources Addressing Interoperability Issues in Digital Libraries
• Administrative Document Analysis and Structure
• Automatic Document Layout Analysis through Relational Machine Learning
• Dataspaces: where structure and schema meet.