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ACL
2007
13 years 9 months ago
A Seed-driven Bottom-up Machine Learning Framework for Extracting Relations of Various Complexity
A minimally supervised machine learning framework is described for extracting relations of various complexity. Bootstrapping starts from a small set of n-ary relation instances as...
Feiyu Xu, Hans Uszkoreit, Hong Li
LREC
2008
125views Education» more  LREC 2008»
13 years 9 months ago
Adaptation of Relation Extraction Rules to New Domains
This paper presents various strategies for improving the extraction performance of less prominent relations with the help of the rules learned for similar relations, for which lar...
Feiyu Xu, Hans Uszkoreit, Hong Li, Niko Felger
LREC
2008
160views Education» more  LREC 2008»
13 years 9 months ago
Automatic Extraction of Textual Elements from News Web Pages
In this paper we present an algorithm for automatic extraction of textual elements, namely titles and full text, associated with news stories in news web pages. We propose a super...
Hossam Ibrahim, Kareem Darwish, Abdel-Rahim Madany
EMNLP
2010
13 years 5 months ago
A Semi-Supervised Method to Learn and Construct Taxonomies Using the Web
Although many algorithms have been developed to harvest lexical resources, few organize the mined terms into taxonomies. We propose (1) a semi-supervised algorithm that uses a roo...
Zornitsa Kozareva, Eduard H. Hovy
CICLING
2010
Springer
14 years 2 months ago
Multi-view Bootstrapping for Relation Extraction by Exploring Web Features and Linguistic Features
Binary semantic relation extraction from Wikipedia is particularly useful for various NLP and Web applications. Currently frequent pattern miningbased methods and syntactic analysi...
Yulan Yan, Haibo Li, Yutaka Matsuo, Mitsuru Ishizu...