%A Zhang Zhixiong,Wu Zhenxin,Liu Jianhua,Xu Jian,Hong Na,Zhao Qi %T Analysis of State-of-the-Art Knowledge Extraction Technologies %0 Journal Article %D 2008 %J Data Analysis and Knowledge Discovery %R 10.11925/infotech.1003-3513.2008.08.01 %P 2-11 %V 24 %N 8 %U {https://manu44.magtech.com.cn/Jwk_infotech_wk3/CN/abstract/article_617.shtml} %8 2008-08-25 %X

 Based on the analysis of some state-of-the-art knowledge extraction systems, i.e., MnM, KIM, Text2Onto, Amilcare and Melita, it brings forward that two kinds of technologies, i.e., machine learning and natural language analysis, are developed respectively and get benefits from the inter-reference. On machine learning aspect, some new methods, such as Adaptive Information Extraction, Open Information Extraction, are put forward and have a trend toward Ontology Learning. On nature language analysis aspect, the methods of Pattern-Based Annotation and Semantic Annotation get more attention than ever, and have a trend toward Ontology Based Information Extraction. Besides, Controlled Language Information Extraction method is introduced to reduce the cost of Ontology Construction and allow non-specialists to create or edit ontological data using simple nature language.