On-Line Extraction Rule Analysis

摘要

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 differs greatly according to its input: from unrestricted free-text to semi-structured Web documents. This paper extends an automatic pattern discovery approach called IEPAD 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. Evaluation results show a high level of system performance.