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Annotation Free Information Extraction from Semi-structured Documents
BibTeX
@MISC{Chang_annotationfree,
author = {Chia-hui Chang and Shih-chien Kuo},
title = {Annotation Free Information Extraction from Semi-structured Documents},
year = {}
}
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Abstract
The vast amount of online information available has led to renewed interest in information extraction (IE) systems that analyze input documents to produce a structured representation of selected information from the documents. However, the design of an IE system di#ers greatly according to its input: from unrestricted free-text to semi-structured Web documents. This paper introduces OLERA -- OnLine Extraction Rule Analysis to the rapid generation of IE systems that can extract structured data from semi-structured Web documents. In this novel framework, extraction rules can be trained not only from a multiple-record Web page but also from multiple single-record Web pages (called singular pages). Most of all, this framework requires no annotation labor that is required for many machine-learning based approaches.
Keyphrases
semi-structured document annotation free information extraction ie system semi-structured web document extraction rule annotation labor multiple single-record web page structured representation online information many machine-learning novel framework singular page input document information extraction multiple-record web page rapid generation vast amount olera online extraction rule analysis
