Knowledge Integration Across Multiple Texts

被引：0

作者：

Kim, Doo Soon ^{[1
]}

Barker, Ken ^{[1
]}

Porter, Bruce ^{[1
]}

机构：

[1] Univ Texas Austin, Dept Comp Sci, Austin, TX 78712 USA

来源：

K-CAP'09: PROCEEDINGS OF THE FIFTH INTERNATIONAL CONFERENCE ON KNOWLEDGE CAPTURE | 2009年

关键词：

knowledge acquisition; knowledge integration; natural language understanding; learning-by-reading;

D O I：

暂无

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

One of the grand challenges of AI is to build systems that learn by reading. The ideal system would construct a rich knowledge base capable of automated reasoning. We have built a Learning-by-Reading system and this paper focuses on one aspect of it: the task of integrating together snippets of knowledge drawn from multiple texts to build a single coherent knowledge base. Our evaluation shows that our approach to the knowledge integration is both feasible and promising.

引用

页码：49 / 56

页数：8

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