Information Extraction from the Web: System and Techniques

作者:Luo Xiao, Dieter Wissmann, Michael Brown, Stephan Jablonski

摘要

Information Extraction (IE) systems that can exploit the vast source of textual information that is the internet would provide a revolutionary step forward in terms of delivering large volumes of content cheaply and precisely, thus enabling a wide range of new knowledge driven applications and services. However, despite this enormous potential, few IE systems have successfully made the transition from laboratory to commercial application. The reason may be a purely practical one—to build useable, scaleable IE systems requires bringing together a range of different technologies as well as providing clear and reproducible guidelines as to how to collectively configure and deploy those technologies.

论文关键词:information extraction, machine learning, knowledge acquisition, internet applications, methodology and design

论文评审过程:

论文官网地址:https://doi.org/10.1023/B:APIN.0000033637.51909.04