文章基本信息

标题：Extraction of Structured Information by Machine Learning Using Community Information
本地全文：下载
作者：Noriyuki Morichika ; Masahiro Hamasaki ; Akihiro Kameda 等
期刊名称：人工知能学会論文誌
印刷版ISSN：1346-0714
电子版ISSN：1346-8030
出版年度：2011
卷号：26
期号：2
页码：335-340
DOI：10.1527/tjsai.26.335
出版社：The Japanese Society for Artificial Intelligence
摘要：In this paper, we describe our approach for information extraction from documents, which is based on supervised machine learning and collective intelligence approach. This approach is aimed at redeeming each method, because each method has merits and demerits. It provides various ways for users to input data to improve information extraction. Users can add not only supervised data but also a rule to extract values for a set of attributes. Various ways to input data allows many users to add a lot of data for quality improvement and machine learning can reduce noise of data input by users. We implemented it in event-information extraction system, and the experimental result shows effectiveness in correctness and convenience.
关键词：information extraction ; machine learning ; collective intelligence